It’s a mapping survey carried out on World Diabetes Day which was held on 14 November.

It aims to show how mapping tools can easily enable an overview of stakeholders to be drawn up for a short event, as well as the keywords used to mention an event.

 1) Collection elements

The items mentioned in the maps below are tweets. Collected through several linking statements, all the tweets (well, a maximum number of tweets) were mined since they comprise one of the following keywords:

• diabetes
• #wdd, which is the official hashtag of World Diabetes Day
• Diabeticos
• Diabetic
• Diabetes
• 糖尿病
• 糖尿病患者
• diabetique
• diabetiker

It’s therefore a collection covering a fairly large number of languages if it is borne in mind that the word diabetes is written in the same way in a very large number of Romance languages.

Thus we collected 36,500 tweets over 3 days (13, 14 and 15 November), of which more than 20,000 were posted on World Diabetes Day, demonstrating the high level of activity linked very closely to the event.

In addition, the act of extending the collection to words other than the single word WDD enables us to reconstruct the event in its Twitter ecosystem, bearing in mind that the majority of average Twitter users are not particularly familiar with hashtags and are probably even less aware of the official WDD hashtag. As diabetes is a matter of concern to the general public, it is  vital to be open about the query so as to reproduce the most faithful image of posts about WDD, even if the latter comprise neither the hashtag nor the word WDD.

2) The most active accounts

The very simple graph below enables us to spot the 30 main Twitter accounts that posted on this subject.

Reading the graph lets us make out the existence of two fairly large and fairly close clusters in light blue and yellow. The yellow cluster is the one which is formed around the official WDD account with the DiabetesUK account and JDRFUK nearby.

Reading each of these accounts enables easy identification of the topic’s key players and recognition that even quite obscure accounts have an interest in and are active on the topic.

• Am I Diabetic forum / portal
• The charitable organisation www.diabetes.org.uk
• Manny Hernandez (AskManny), blogger specialising in health and charitable organisations
• Cherise Shockley aka SweeterCherise, “living with diabetes and social media enthusiast”
• Novonordisktbl, diabetes products specialist (micro-needles)
• etc.

In short, there are many spokespersons for diabetes and World Diabetes Day: manufacturers, associations, organisations, private people / persons, with the latter comprising some people who are particularly active on social media, etc.

Lists of accounts in a clickable Excel format can thus be easily built up.

Here are the top 100 accounts dealing with this topic in terms of number of tweets.

 3) Analysis of the accounts and their relationships

It is nevertheless of interest to note that a large number of clusters is shown on this map even though the most active people on the same topic generally account for a limited number of clusters. This is due to the very international generic term diabetes (and thus for the leaders in each country being kept relatively far apart due to the constraint of language) and also by the wide variety of people concerned that changes within the various circles.

The above map gives a good overall view of the topics of WDD and diabetes over the 3 days of collection. To begin with, it is undeniably a topic for the general public involving a large number of people who feel concerned, but who don’t necessarily exchange views using obvious accounts on the topic or ones that are identified with it. This is shown well by the size of the central bubble that comprises the less active accounts.

Then we notice a very compact community on the topic with a high level of interactions and very dense criss-crossed links. These active and similar accounts reach several layers of people and their messages thus manage to spread and produce interactions between the various layers of groups of people or micro-communities.

It must be noted that the the community is not normally so densely linked. Here a clustering of accounts is observed around the WDD account, including those in various languages. The change observed in a mapping analysis before WDD and during WDD clearly shows that the WDD account and the event in general is therefore deeply unifying and moreover that it contributes considerably to increasing the volume about the theme of diabetes.

The map above shows accounts that posted at least 5 times on the theme during the period, as well as the network they produced (existing interactions).

This very interesting view enables recognition of the fact that the most active accounts manage to reach out and give rise interaction and not that they form a closed community. It is obvious here that they managed to produce interactions since, with 605 accounts having tweeted more than 4 times, this is 2,840 accounts forming a continuous network of interactions shown on our topic.

Several things can be observed on this map:

• The influence of social media influencers on the topic of diabetes in the dark blue cluster, to which the manufacturer NovoNordisk is also linked and is established as an account “spreading” conversations: it resends mentions or retweets by other Twitter accounts, trying to increase its visibility amongst the “leaders” in this way.
• The WDD account received a large number of mentions and the penetration of its messages through chains of retweets on several levels can be clearly seen. It was a relatively successful public relations exercise, but one which also worked well due to the existence of accounts on the topic that are already established and which themselves become points of visibility and real audience forums.
• We also observe uncharacteristic points on the graph: small in size, they posted few tweets but gave rise to several conversations. This is shown by the number of links pointing to this account. Take the example of AmeliaLilyOffic, which produced several dozen interactions whilst she only posted two tweets on the subject. These tweets were retweeted by both people and organisations. This shows that the strategy aimed at gaining the support people known to the general public and affected by the disease for a possible endorsement is a winning strategy. This visibility of celebrity accounts, whatever the topic, is a permanent feature on social media.

• The Am I Diabetic account which, although it posted a lot, managed to produce few interactions… (little interest if any…)
• The local WDD accounts (WDD_brasil for example) were far less effective and created few interactions. It that case it could  be questioned whether it would be more attractive to have only a single official WDD account. In any event a real job of co-operation and co-ordination must be carried out between local accounts and the WDD account.

• !!! Access the map online, navigable, clickable, searchable !!!

Access the navigation interface inside the large scale network visualisation map of Twitter accounts related to World Diabetes Day 2012 by clicking on the image above

 4) Analysis of hashtags and the relationships between them

The hashtag map enables the hashtags most mentioned together in the same tweet to be spotted.

This analysis enables:

• Rating of the official hashtag’s importance
• The appearance of non-official hashtags to be spotted
• Seeing what associated themes are being addressed during World Diabetes Day

The map below shows the hashtags which were mentioned more than once in the body of the collected tweets. This very simple filter criterion enables us to eliminate the hashtags which are too marginal and are generally the action of a single person which did not give rise to any mention or RT.

It comprises 1,329 hashtags which is a large number if it is borne in mind that the collection request only contained a fairly small number of keywords.

Hashtag maps are more tricky to read since they generally comprise a greater proportion between the nodes (hashtags in this case) and larger edges (joint mentions between hashtags within one and the same tweet here) than other types of map.

However, the map clearly shows a cluster (violet) related to the hashtags for World Diabetes Day in which we can detect amongst others:

• WDD
• WDD2012
• WDD12
• DiabetesAwarenessMonth
• WorldDiabetesDay
• WDDchat12
• StopDiabetes
• DiabeticHero (on the border with the green diabetes cluster)
• Weltdiabetestag
• Diamundialdodiabetes
• blue
• blue day
• raiseawareness
• wearblue
• BGNow
• 247diabetes
• DSMA

Therefore a relatively large number of hashtags can be seen that were rated as being directly linked to the event.

To begin with, there are the various declensions of WWDD, WDD12, WDD2012, etc., which also shows the difficulty of “imposing” an official hashtag and the need to keep an eye on the environment for different names even if a watchword is given.

We can also clearly see the event’s linguistic declensions and that the latter do not produce a linguistic sub-cluster. This is explained by the fact that the noun diabetes is the same in Spanish and German amongst others, and by an overexposure of the English language in this event and probably also by a smaller sub-community of German and Spanish tweeps affected by the topic (in the language in which they were postedin any event!)

In terms of public relations and consequences, the map also enables key events or the associated bodies to be spotted:

• WDDchat12, which aroused a lot of of interest within World Diabetes Day and its association with the DSMA; this is usual since the Diabetes Social Media Advocacy association is the organiser of this chat which took place throughout the day and involved several accounts devoted to diabetes.
• BigBlueTest, a dedicated website, sponsored by Roche, to collect data about the behaviour of diabetics, which was active up to World Diabetes Day. It’s a site that benefited from strong exposure during this event.
• BGNow, a term used by tweeps when they are mentioning their glucose level measurement  at the time, which experienced a high rate of mentions over the period, but with a lesser association with the WDD cluster (it is situated on the border and reveals weak links).
• The4Ts, a campaign about the 4 types of diabetes supported by the singer Amelia Lilly
• etc.

Of course, other clusters than that for WDD are apparent and we can indeed notice the existence of:

• a very dense diabetes cluster (in green) very close to the WDD cluster, meaning that several topics are supported during WDD but are also dealt with outside this isolated event.
• a blue cluster to the right at the top, French.
• other small-sized clusters made up of more marginal hashtags.

For the more inquiring and health or diabetes professionals, you’ll find below the full map of the hashtags collected comprising more than 4,200 terms.

5) Analysis of the relationships between hashtags and accounts

The map below, which is based on the same body of collected tweets, is a map which highlights the relationships between Twitter accounts and hashtags.

The enables identification of the most vigorous promoters of such and such hashtags.

The orange links show the connections between an account and a hashtag. The hashtags are in yellow and the accounts in red. This map comprises  2,287 points, but we concentrated solely on the WDD cluster WDD and eliminated the residual clusters (such as that for diabetes, for example). Note therefore that this means the hashtags related to WDD but not rated as central within the WDD cluster could be eliminated; and this is the case anyway.

A quick reading reveals the following points:

• The AskManny, DiabetesUK, JDRFUK, vero7184,txt4health and (of course) WDD Twitter accounts are the most active in promoting the hashtag #WDD. By the way, we note that the txt4health site is sponsored by the American Diabetes Association and NovoNordisk.
• FatCatAnna is promoting the hashtags WDDChat12 and DSMA relatively strongly. A quick search reveals to us her diabetes activism on the Web and social media.
• DiabetesSocMed, crankypancreasand SweeterCherise are promoting WDDChat12. Would they happen to belong to the same association ???
• Novonordisk is one of the few manufacturers which emerges clearly as a promoter of #WDD (although we can also find Boehringer here, but to a far smaller extent)

For the more inquiring only, once again here’s the complete map below of the accounts and hashtags for the WDD cluster:

6) What conclusions?

First of all, the above analysis is a partial analysis carried out on a large number of tweets. It is vital to understand that the mapping analysis derives all of its interest from answering certain questions and is even more in-depth if you have very specific accounts or hashtags that you wish to study.

What we can observe is that:

• The volumetric effect linked to the event is obvious.
• This event is based on a strong community and already in existence around diabetes
• Manufacturers can promote these events by retweeting or mentioning without communicating directly about their products and thus gain visibility.
• The use of hashtags is still something reserved for “geeks”: hashtags are still only used by a small proportion if lots of people are talking about diabetes on Twitter.
  • The linkage of public relations exercises to the event works well.
  • There is a real community of geeks / social media addicts suffering from diabetes, which has an audience in and an influence on the diabetic community.
  • And there are still other conclusions to be drawn!!!

7) Other sound and instructive reading about data mapping

Articles:

- Bug Facebook and map [French]

- #ereplay map – Or influence visualised [French]

- MISTE competitive intelligence map: WTF??? [French]

- Where it’s a matter of mapping and competitive intelligence… still [French]

- Mapping : don’t turn your brain off by relying on the tools [French]

- Data mapping : Gadget or business tool ? [French]

Business Cases:

• Twitter eRepDay Map [French]
• Twitter Orange Bug Map [French]

Our mapping proposition:

• Comprehensive presentation of Actulligence’s mapping proposition [French]
• Presentation of the dedicated Twitter mapping proposition [French]

Influence is considered first and foremost as one of the analytical keys for  its community ecosystem, clients or even detractors, but also as one of the weighting keys for its opinion leaders whether they’re pro or anti.

I will not return to the notion of influence. It has been defined, redefined and contra-defined whether that involves the academic definition or the online reputation point of view.

For my part, I like defining the influence of an individual or medium as its ability to influence the behaviour of those with whom he or it interacts (reading, conversations, promotion, activism, etc.) What’s more, I don’t think I’m the first to uphold this definition and even less the person who first mentioned it.  Many psychologists or sociologists have drawn up and enhanced this definition by also attempting to determine the levers for exerting influence.

But here’s the problem. If this influence could be easily measured in a vacuum, if it’s conceivable to determine it for a signal that is broadcast and can be accurately and clearly isolated by the person receiving the influence message (typically an advertising campaign specific to a time t), it’s far more difficult at the level of the Web, especially if there may be multiple and varied influence messages.

This then raises the question of the influence measurement for a website, a blog, a tweet or an anonymous person on its or his community of friends.

And although I despise the notion of influence reduced to its pure quantitative analysis, i.e. an artificial figure which is derived from the crude compilation of several observable metrics (number of followers, number of videos posted, number of likes, etc.), I’m forced to admit that Klout is an operational tool that’s far from perfect, but one which  has several advantages for those who wish to have a useful indicator at their disposal.

How Klout works

Let’s remembers first and foremost that Klout is a general indicator which ranges from 1 to 100. At 0, it’s no good dreaming. No buzz marketing, communications or sponsored feature agency will be contacting you. At 100, you’ll have weekends in palaces, champagne and various benefits in kind and of all types.

There are two possibilities so that Klout can calculate this indicator:

• You have a Twitter account and Klout will always be able to score this Twitter account
• You have accounts on other social media sites such as Facebook, Google+, Instagram, Flickr, etc. and Klout will be able to score these accounts if the user is registered with www.klout.com and has given details for these accounts. Ideally he will have given details of several of his social media accounts, which will enable the individual to be scored and not each of the accounts separately for the individual in question.

Consequently, the score is calculated according to the metrics that can be observed on each of these networks, which are measured, combined and regurgitated.

The operational benefits that can be gained from using Klout can be easily realised:

• The metric is the same for all social media or for any combination of social media accounts. Although it’s not perfect, it makes comparison easy and although there is a risk of adding apples to oranges to work out the captain’s age, it has the merit of being  feasible. All you have to do afterwards is “rectify”,  a method familiar to apprentice analysts. So Klout clearly relies on its knowledge for the weighting coefficients derived from its observations for the weight of each of the networks in the final score. In addition, it took steps this February to make an adjustment to these coefficients which is likely turn up in the next few months.
• If you make an evaluation the name of a brand or major consumer product, the proportion of tweets in the number of quotations for the above-mentioned brand is between 30 and 60 %. The fact of being able to scoring any Twitter account is an advantage for those who want to be found in the tidal wave of tweets and want to discern the difference between the nobody and THE Influencer.
• Klout is moving increasingly towards “influence gaming”. By offering an in-house Klout points system, Klout is injecting its own scoring factors endogenous to its solution. Although it must be regarded as a potential skewing of influence scoring outside Klout, this strategy includes other advantages for Klout, adding to its scoring system greater numbers of users who must register to benefit from it and who have the additional possibility of describing each of the users of Klout thematically. Klout is thus attempting to link quantitative influence analysis and influence themes via a qualitative segmentation of its users that they themselves provide. (By distributing Klout points to other Klout users or by characterising a Klout user on a on a theme area, I have more chance of gaining Klout points Klout or being classified by theme by a third party.)

Klout and APIs

As with all so-called Web 2 solutions which are riding high, Klout has developed its own APIs (Application Programming Interfaces).

It is undeniably one of the points which makes Klout a solution that enables a large-scale roll-out of measuring the influence of content producing internet users to be envisaged.

And, of course, the point of this post was to show you what it is possible to do with Klout’s APIs.

An API enables data to be sent to a third party solution and for it to be asked to process this data within its system and to send the completed results of the processing to be sent back to you.

Without going into details, an API enables a vendor such as Klout to:

• Enhance its ecosystem of solutions based on its database and its technologies by facilitating interactions with the latter (this has been the strength of Twitter for example, which has been able to speed up its development by leaving the task of developing software or Web interfaces for its infrastructure and its data to others .)
• Control who does what with its data. By opening up the APIs, solutions such as Klout or Twitter need to establish each other’s identity to be able to interact with the data. This enables them to know who’s doing what, to control quotas and incidentally to monetise them eventually.
• Standardise the way of interacting with the data. APIs are in fact always supplied with directions for use.
• Democratise the solution offered by increasing its exposure to the general public.
• Remain in control of its primary data which is no longer duplicated but called upon.

Consequently, before working with Klout’s APIs, you’ll need to apply for an identifying API key that you’ll need for all interactions with Klout’s infrastructure and, if you’re brave enough, you’ll have to study the documentation (V1 of the Klout API should be done away with in the near future, but V2 is still only in beta).

What do Klout’s APIs enable?

Klout’s APIs enable different items of information to be obtained, such as:

• An account’s score using a a name or a list of Twitter account names;
• The type of influencer that a user is (Klout defines 4 major types of influencers according to their posting activity, their retweet rate, the structure of their audience, etc.);
• The subject on which a person is a user;
• The people who influence a user or group of users;
• The people who are influenced by a user or group of users.

Klout’s APIs have some more not insignificant advantages which are using GET and providing the output data in XML format or JSON format. (For novices, XML has the advantage that it can be opened with most of the latest versions of Excel type spreadsheet programs.)

Practical exercise

Basically, this is how we could set about getting a nice Excel score file for the accounts held by Bouygues Télécom.

1. Identification of the accounts via Twitter search that, for a simple “Bouygues Télécom” request, supplies us easily enough with the following accounts: bouyguestelecom, Helena_tel, b_and_you, bouyguestel, bouyguesnews
2. Sending a request via Klout’s API for all these accounts, which quite simply gives us a URL for keying into a browser which looks like this: http://api.klout.com/1/klout.xml?users=bouyguestelecom%2CHelena_tel%2Cb_and_you%2Cbouyguestel%2Cbouyguesnews&key=PUT_YOUR_API_KEY_HERE
3. Getting the results back in XML format which will give you the elements below for the score, for example:

<?xml version=”1.0″ encoding=”UTF-8″?>
<users>
<user>
<twitter_screen_name>bouyguestelecom</twitter_screen_name>
<kscore>57.96</kscore>
</user>
<user>
<twitter_screen_name>Helena_tel</twitter_screen_name>
<kscore>29.41</kscore>
</user>
<user>
<twitter_screen_name>b_and_you</twitter_screen_name>
<kscore>59.92</kscore>
</user>
<user>
<twitter_screen_name>bouyguesnews</twitter_screen_name>
<kscore>10.77</kscore>
</user>
</users>

which you will then be able to import very simply by saving it in Notepad with an XML extension and opening it in Excel for example. For those who are more geeky, a direct import into a MySQL or other database is also relatively straightforward via libraries such as, for example, PHP XML Library, Magic Parser in PHP and similar libraries available in the most common programming languages or provided directly by these same languages.

As the number of “scorable” accounts in a single call is relatively high (limited by the length of the GET URL), you can easily implement a simple, low-cost solution developed in-house to enhance the content collected by an online reputation system.

To do even more, it’s also possible for you to go down the networks modeling and mapping route by relying on two methods which enable you to find out the influencers and those who are influenced from a list of Twitter accounts sent to the API. A little processing loop and there you are, busy building up a structured and scored database of Twitter accounts. For producing a map of its ecosystem, for example?

Below is an example for Bouygues Télécom’s accounts using the command “influencer of”:

<?xml version=”1.0″ encoding=”UTF-8″?>
<users>
<user>
<twitter_screen_name>
<screen_name>bouyguestelecom</screen_name>
<twitter_id>16557431</twitter_id>
</twitter_screen_name>
<influencees>
<twitter_screen_name>littletiger8</twitter_screen_name>
<kscore>19.27</kscore>
<twitter_screen_name>arsceniq</twitter_screen_name>
<kscore>16.49</kscore>
<twitter_screen_name>klabecot</twitter_screen_name>
<kscore>16.05</kscore>
<twitter_screen_name>matartine</twitter_screen_name>
<kscore>15.44</kscore>
<twitter_screen_name>mister_tropical</twitter_screen_name>
<kscore>14.99</kscore>
</influencees>
</user>
<user>
<twitter_screen_name>
<screen_name>Helena_tel</screen_name>
<twitter_id>34608636</twitter_id>
</twitter_screen_name>
<influencees>
<twitter_screen_name>ruzzan</twitter_screen_name>
<kscore>41.05</kscore>
<twitter_screen_name>echosdunet</twitter_screen_name>
<kscore>37.32</kscore>
<twitter_screen_name>le_koala_motard</twitter_screen_name>
<kscore>35.09</kscore>
<twitter_screen_name>fondationbytel</twitter_screen_name>
<kscore>33.92</kscore>
<twitter_screen_name>groupebouygues</twitter_screen_name>
<kscore>29.7</kscore>
</influencees>
</user>
<user>
<twitter_screen_name>
<screen_name>b_and_you</screen_name>
<twitter_id>323325885</twitter_id>
</twitter_screen_name>
<influencees>
<twitter_screen_name>zedeme</twitter_screen_name>
<kscore>28.26</kscore>
<twitter_screen_name>kefdef</twitter_screen_name>
<kscore>20.66</kscore>
<twitter_screen_name>behold_me</twitter_screen_name>
<kscore>20.17</kscore>
<twitter_screen_name>danielelkouby</twitter_screen_name>
<kscore>18.67</kscore>
<twitter_screen_name>dsccreation</twitter_screen_name>
<kscore>18.61</kscore>
</influencees>
</user>
<user>
<twitter_screen_name>
<screen_name>bouyguesnews</screen_name>
<twitter_id>130888957</twitter_id>
</twitter_screen_name>
<influencees>
<twitter_screen_name>craig2169</twitter_screen_name>
<kscore>32.74</kscore>
</influencees>
</user>
</users>

which shows us for example from a quick glance that the BouyguesTelecom account reaches the general public, whereas the Helena_Tel account is mainly picked up by incestuous, made in Bouygues accounts and Echos du Net (and by two other accounts).

Conclusion
Klout is not a panacea for measuring influence in the smallest socio-psycho-societal and website nook and cranny, BUT Klout, and its APIs in particular, have their place in online reputation strategies and particularly in those that have to process a large number of  contacts and amounts of content.

Klout is imprecise, Klout gives a general picture, Klout is simplistic, but Klout provides some answers, however imperfect they may be, whereas others only provide questions.

Moreover, as they are built – very simply – around a GET call, Klout’s APIs are easy to implement and integrate, with the results being based on two of major data exchange standards, JSON and GET.

In addition, a small detail that will interest lovers of Social Media Monitoring solutions, Radian6 has accepted Klout as its influence scoring solution and has integrated it into its Desktop interface (Radian 6 Engagement Console) and online.

Furthermore, let’s not forget that the best way of knowing your influencers is to have human knowledge, with tools such as Klout then enabling checks to be carried out beyond the bounds of its knowledge, the carrying out of consistency checks or random checks, or even discovering new potential influencers.

Going further
There are other influence indices such as:

• PeerIndex, made in Europa, likewise offering APIs
• Kred which claims transparency for its index and its way of compiling it, and which also provides APIs.

Nevertheless, as far as I’m concerned, I find that the Klout APIs offer more possibilities.

Anyway, these RSS URLs have not completely vanished into nothingness. The URLs are still usable, but you’ll need to know their structure so you’ll then be able to add them to your newsreader or monitoring software.

Let’s imagine you do a search on the word “KEY_WORD”, your RSS feeds will look like this:

http://search.twitter.com/search.atom?q= KEY_WORD

It is also possible for you to include a filter by language in the results:

http://search.twitter.com/search.atom?lang=fr&q=KEY _WORD (for English, use en instead of fr.)

Searching for two key words is hardly more complicated:

http://search.twitter.com/search.atom?q=KEY_WORD+KEY _WORD2

By knowing a little about the conversion of characters and advanced operators, you can also reconstruct its RSS URLs quite easily; for example, for a request such as “competitive intelligence” OR “strategic monitoring”, you’ll get the following RSS URL:

http://search.twitter.com/search.atom?lang=fr&q=%22intelligence%20%C3%A9conomique%22%7C%22veille%20strat%C3%A9gique%22

More simply, to re-form a RSS URL very easily: do a search using the Twitter search engine that’s available at http://twitter.com/#!/search-home

And add right what you’ve just copied right in front of it: http://search.twitter.com/search.atom?q= , which finally gives the URL previously shown: http://search.twitter.com/search.atom?lang=fr&q=%22intelligence%20%C3%A9conomique%22%7C%22veille%20strat%C3%A9gique%22

That was today’s very useful tip and trick. Simple and effective.

Some time ago I published the same tip and trick on Flickr in the same style with these two posts: Tag Flickr and RSS [FR] and Going further with Flickr’s APIs [FR]

I turned down this invitation for various reasons that have absolutely nothing to do with the purpose of this post. The fact remains that the subject interests me and it seemed pertinent to me to take the time to answer this question.

I’m not a soothsayer and consider myself even less to be a guru, so these predictions will obviously need to be taken for what they are: my vision, or even my desires or my illusions of what monitoring could become in 2011 and, let’s go mad, perhaps even in 2012.

1) Monitoring devoted to creating value

The Anglo-Saxon vision of monitoring is rationalist. It’s often based on figures, factual and formal data that can be extracted from the Web or any other information source. It enables the feeding of internal databases, wikis, and Information and Decision Aid Systems in the Business Intelligence sense of the term and the making of essential business decisions: a decision to partner with another business with a view to buyout or merger, estimating the production capacities that will need to be called upon and in particular assessing the quantity / price pair and do all of this by geographical area.

In Anglo-Saxon countries monitoring is also the often distinct organisational difference “business analysts” and  “information researchers”. The “information researchers” thus enable the business analysts to dispel certain shadows connected with a specific market analysis problem. Consequently, the creation of value linked to analysis and the decision-making it enables is a vertically tiered chain in which the information search specialist has very specific expertise enabling him to define a request for information, to implement it and communicate its results in an optimum form. He knows his market, does the analyst; he has gained a perceptive knowledge of its workings and its protagonists. This knowledge resulting from his cultural integration and experience in the sector enables him to give value in full measure to the information supplied to him.

The French monitoring landscape is hopelessly devoid of real information researchers and top flight monitors. Degrees stamped ‘monitoring’ are rarely awarded and all the competitive intelligence research fellows aim to be analysts or strategists, but few of them are not afraid to poke their noses into the tools. This is not new; craft industry is rotten in France. The software is too. The rationalisation of monitoring, alongside which the term strategic is frequently placed, or which is renamed competitive intelligence, has dug a chasm between the information and those who need it (the analysts and strategists). The information footsoldiers, those who roll up their sleeves to go looking for it, have deserted the ranks of an army in which the generals have multiplied by caring little about hiring those with good qualifications to help them draw their maps and put the finishing touches to their plans.

Let’s add to this the myth of the productive, divinatory and semantic magic tool, which will work with an improbable degree of autonomy that only exists in Powerpoints or marketing brochures that make a point of erasing all signs of staffing and any assessment of time and people.

I believe, I hope at least, that 2012 or 2013 will bring about a reassessment of the role of “information researcher” and more if things go well. A reassessment that will be recognised in the working of collaborative processes and not in an unhealthy approach of contracting out that is sometimes the defect of Anglo-Saxon style CI systems.

Monitoring is an which is one of the key points of competitive intelligence. 2012 the year of monitoring?

2) Monitoring structured (finally!)

Let’s look at the Anglo-Saxon side once again and search out monitoring platforms or monitoring software, those that resemble a Digimind or an Ami Software product or furthermore those of KIM (Arisem).

They are rare…

You can sense it, to justify the ROI from monitoring, the Holy Grail which opens the doors to a pay rise and the unfreezing of budgets, we need figures. Figures on competitors, figures about the market.

If there are no figures we need information that can be processed, or rather understood, and do all this while adapting to a mass of information which hasn’t stopped bamboozling us and forcing us to invent new, more productive, more “clairvoyant” information processing tools.

Across the Atlantic they speak of Web Scraping, or even of Web Harvesting. It has long been understood that the gathering of text-based documents was treating business in an intellectual way. The small pleasure which comes back to reading your newspaper in the morning with your coffee.

There’s another sign that’s never wrong. Google gives it us.

Google Squared which structures the data on the fly with varying degrees of success, Google once again which includes micro-formats enabling the structuring of information at the very source. Most recently there’s Google Refine.

RSS has clearly shown the power of structuring and standardising information. And yet the structural organisation of RSS is light. Let’s imagine the same thing, but with many more fields. It would admittedly be more difficult to implement, but also far more powerful.

To structure monitoring data closest to the source is to ensure its maximum usability. It’s also to ensure its mobility, its transmissibility.

2012 will be the year of the database for monitoring.

3) Monitoring funded

Many French companies are trying their hand at monitoring today. They are having a go at it with varying degrees of success.

And like many trial projects, they’re being done on tiptoe. We get the measure of it. We ask for a ridiculous or minimum investment and expect a colossal ROI.

There are many guilty parties:

• The institutions who financed projects of a rather mediocre quality without a real analysis of the need, and I’m thinking as a priority of projects I could see in some competitive hubs that were often undersized for dealing with a heterogeneity of requires, types of users and uses.
• The Competitive Intelligence “headliners” that I regularly hear saying that competitive intelligence and monitoring are states of mind. That you can do low-cost monitoring and Competitive Intelligence. Yes you can. You can also try doing the Paris Dakar with a DS (the car, not the console…). At any rate, you’ll have little chance of winning the race. You can also hire people with a baccalaureate + 5 at € 28K  per year by asking them to be able to speak 3 languages (but 4 would be a plus) to be cutting edge monitors and analysts in their souls. You can. However, it is more certain that by doing so, you’d be building a gallows for yourself by putting potentially volatile teams at the heart of your approach.
• Training courses pointing up Netvibes and Google Alerts without offering any other perspective on tools for competitive intelligence, text mining, … and which spread the myth of everything for free.

No. Competitive intelligence, it needs money and effort. It’s an investment and an investment is built up over the long term.

And if 2012 were year of the real well-built, properly budgeted, designed and scaled competitive intelligence and monitoring project?

4) Monitoring accepted
And here it’s more than a vision, it’s a news item.

The frenchstandard AFNOR XP-X-50-053, an experimental standard, is getting long in the tooth.

In the next few weeks new documents from AFNOR on monitoring and competitive intelligence should see the light of day. They’ve been in preparation for more than one year.

I can’t help but admit that I have my doubts about the opposability and acceptance of these documents, but the unrelenting race that Bernard Carayon, Hervé Séveno and Olivier Buquen seem running to have the last word about how they’ll improve the regulation a profession that clearly appears to worry them could indeed find an outcome in standardisation.

2012 for monitoring: a year of order? No… I’d really like it, but unfortunately I honestly don’t think so.

5) Monitoring revived
The signs are there. They can’t be ignored.

The expansion of the Martre report has indeed been lived through, but the entry barriers set up long ago are beginning to give way.

The younger generation cannot be ignored any more even if it means hurting a few egos that have been treated gently for far too long.

The exchanges have been lively in the last 6 months.

To see Bernard Besson and André Added of the IFIE invite the younger generation to talks and at the same time launch themselves as Business Angels for the young shoots in competitive intelligence. Wow. I didn’t think I’d see it in my lifetime.

The only thing we’ll be missing is seeing Hervé Séveno as concerned about defending young professionals as being consulted by Olivier Buquent and then perhaps we can finally say that competitive intelligence and monitoring are not a generational invention but rather a tool that works for businesses.

2012, year of dialogue and renewal for ET monitoring for competitive intelligence.

What wishful thinking. What hopes. Perhaps some won’t see the light of day in 2012. Perhaps I’m also fooling myself about some of them.

But if there’s one thing about which I’m convinced regarding monitoring, it’s that it’s absolutely essential work. I’m also convinced that it’s an enthusiast’s job. If there’s a profession where lifelong training comes into its own, it’s our profession. It takes up our evenings, sometimes our weekends and information often goes with us wherever we are.

It’s a job that I’ve had for many years now, which has led to my meeting people of great worth, some of them having been amongst the first bloggers such as Christophe Deschamps or Christophe Asselin, others much more recently qualified, some even having been my students and who I look upon as friends today.

All have this liking for information. Most consider their work as a source of perpetual discovery.

What I want for monitoring is that it continues to arouse passions and to create vocations in 2012 and beyond.

This takes me straight – subtle change here – to a brief look at image search.

I’m assuming you’ve heard about the fuss about the man without swimming trunks on running into the water that an absent-minded photographer forgot to crop out when editing. There’s a fuss, more fuss and yet more fuss… and incidentally the journalist involved has probably caused the biggest peak in traffic experienced by La Redoute’s site in the last decade.

So, we can measure the fuss with appropriate monitoring / online reputation / social media monitoring tools. And that works well with fusses that are text-based. But in this instance here the very core of the fuss is based around an image.
So, how can this image and its misappropriations be tracked then?

Before we would have typed “La redoute” into Google images, perhaps adding filtering by date…But that wouldn’t have worked well.

A search for one week of the type: fuss AND “la redoute” provides more appropriate results, but these still have a large element of noise.

Fortunately, from now on Google offers the possibility of uploading an image or even entering its address and then seeing if there are images based on it that have been created, subverted or redistributed. This can be done right next to the button on Google Images for inputting keywords:

All we have to do now is give Google with a suitable image (the original one or even one that’s already been subverted); this one for example:

And then by a miracle of technology, you’ll find the images that Google has in its database that are based on this initial image.

The proof:

A miracle of technology indeed.

Google sceptics will tell me that it’s not the first to do that, to which I will retort far from it and also say that I had dealt with the case of the www.tineye.com search engine or even Retrievr, amongst others in this old article, “Image search by similarity [FR]”.

However, it is clear:

1. That Google has managed the feat of achieving something impressive with an index of a size that’s more than substantial, all at the disposal of the general public,

2. That Tineye doesn’t work (and what’s more that’s what led me to Google). I tested it on the same search and got the small matter of… 0 results.

Here it is, a simple and effective tool working for community managers who want to be able to search for an image by using an image. I won’t say anything more, but there’s a pseudo-European French-speaking/French multimedia search technologies pseudo-project that would do well to wake up a little.

Other possible uses for this search engine :

• to track forgeries of your photographic works or at the very least their illicit commercial use and commercialisation
• to track and identify improper use of your logo
• and generally also to identify logo busting attempts (that is, if the hijacked logo has been created from your original official logo). Of course, you need to understand that what Google searches for first and foremost is a file that has the same “signature”.

I could have written 5h1t: I could have been more subtle; I could have tried to be more consensual; but that must be lacking in my DNA . But in the end by using S-word, I am ultimately being very mild-mannered compared with what I think deep down.
Curation here, curation there. You really wonder if people are speaking through their noses or even from the bottom of a place where the said substance rightly ends up.
I won’t use the word again. It’s ugly enough in French and I don’t even want to think about where it came from in English…Let’s not judge a book by its cover; let’s see what it has beneath the flyleaf…
Because it’s the bottom in which you’re interested, you the bold reader who will have jumped on this vile and eye-catching title, given that you read things properly.
Therefore let’s continue with what’s eye-catching by giving in to that obsession known as counting. I am consequently going to list 5 reasons mean that curation is revoltingly bad, in my view at any rate.

1) Curation platforms and the action of curating in itself contribute nothing

To curate (or to pick out in fact… I don’t know…), what is it? It’s to subscribe to sources of information, read blogs, websites and to choose extracts and content that you will be aggregating in one and the same space.

The action of curating is one that has a very, very, very low added value!.  The proof of this is: it could be fully automated… Selection and enhancement of sources by automated keywords, selection of extracts by contextual keywords and publication. Everything can be done by a machine.

Now you white knights of curation are certainly going to respond that the automated operation is never as relevant as the human one, that what is attractive is this relevant bespoke selection, and these possibilities for subscribing to another’s content; but let’s look reality in the eye. This is not so. And even if it were so, other devices and other solutions that can do that have already existed for many months, if not years, and in my opinion they can do it better…
I have ultimately not managed to find one ounce of added value in curation.

Curation is a content copy and paste system for layabouts, which leads me straight on to point number 2.

2) Curation represents an infringement of copyright

Curation is the taking content from one place and putting it in another. Nothing else. Let’s remember this now – taking content without having permission to do so is an infringement of copyright. Only the right of quotation can be applied, but the latter is subject to a specific procedure which is never observed on curation platforms.
Curation platforms do admittedly also enable the composition of content and the summarising of an article, BUT nobody does it as it’s so simple to copy and redistribute and not to create.

Many people are guilty of that:

• Internet users who redistribute content and infringe intellectual property, the majority of whom in their defence are not in business and don’t make any money, but are only trying to be noticed.Disgraceful, but from the moment that you copy original content from a blog, you nevertheless risk very little if the blog is not a trade blog, since in most instances French justice requires compensation on the basis of the loss incurred.

• Companies who provide the solution and who are paid on an advertising model. Of course, they’re not arms dealers who are making a killing. To repeat the debatable metaphor of an internet monitoring software vendor, the photocopier salesman doesn’t make unauthorised copies of course … but in this present case and even in spite of the clearance procedure linked to hosting activities, it is obvious that the business model of the curation platforms is based on the monetisation of copyright infringement and is therefore disgraceful and reprehensible.

Additional reading: Blogger and author: where are the rights? [FR] which addressed the issues of copyright and Creative Commons licensing fairly broadly.

3) Curation platforms encourage economic freeloading 

Some curation platforms go much further than a tweet which links directly to the original content. Some curation platforms offer the “share” functionality for redistribution on various social networks by linking to the curation platform hosting the content rather than to the original article. It is therefore a harnessing of potential traffic and, as a result, economic freeloading.
What is more, it distances the reader from the author (in quite banal terms of clicks, but also therefore of identification).
Finally, rather than encouraging the exposure of the original content via social sharing mechanisms, the curation platforms encourage their own visibility by offering a specific URL for the copied content whilst maintaining its fine detail (by this I mean that it doesn’t point towards a curator’s account but to the post- based content. Example here.

4) For us, the children of the web, encouraging curation is being irresponsible

Curation does not encourage the accessibility of content. Definitely not. The social mechanisms integrated in the majority of curation platforms are as insubstantial as the elastic on a thong… and what’s more, even here they rely on other social network solutions that have built and and invented mechanisms for the online management of social relationships, which are relatively complete if not innovative.
While Google is juggling to maintain the quality of its results, we should ask ourselves if the extent to which all these mechanisms we are feeding is helping to make the information that we’re looking for inaccessible.
Instead of looking for excuses by saying, “Yes, but there is already too much information, we need to conduct a sectorial analysis of the web by social cluster so as to have easier access to it”, we need to realise

instead that we’re busy treating the plague with a strain of cholera.
Finally, I find it amazing today to come across information professionals who have at times campaigned for sharing creative works in the form of CCommons licensing and are not even worried about knowing (for certain) whether or not they are infringing Ccommons.

5) Curation is drowning the information

We are in a phase of infobesity. No, it’s not an illusion. And no, it has never been so intense. It’s all well and good to record emails received, requests for information and the size of our hard drives. The tools enabling information processing are admittedly improving, but there are delays in their deployment, it takes time to get to know them and they’re not developing as quickly as the growth of information.
In addition, the world in which we are living is finite. The hard disks we produce and the energy we use for storing this information: all of that requires real resources in terms of goods, raw materials, energy; and unfortunately information is tending to achieve rates of growth today whose graph is approaching a vertical line and runs counter to the finite world in which we are living.
To encourage the use of solutions that contribute nothing to information management and take advantage of information technology to increase the amount of information to infinity is to be guilty of leading to the collapse of a system which is based on an operation verging on the worst practices of the financial sector.

In addition, I hope the business angels won’t be taken in by it and won’t encourage businesses whose business model is based on very unsound ground as far as I’m concerned.

Au lieu de se chercher des excuses en disant : “oui mais il y a déjà trop d’information, il faut passer par une segmentation du web par grappe sociale pour y avoir plus facilement accès” il faudrait plutôt se dire que nous sommes en train de soigner la peste avec une souche de choléra.

Finalement aujourd’hui je trouve surprenant de trouver des professionnels de l’information qui ont parfois milité pour le partage de la création sous forme de licence CCommon et ne se préoccupent même plus de savoir (pour certains) s’ils n’enfreignent pas les CCommons.

Conclusion

Today it seems to me to be vital to revert to a saner and more reasoned model for sharing information.
Let’s look at ourselves in the mirror and ask ourselves what we are contributing by redistributing information. I think that if we have nothing interesting to say or post, it would in any event be better to refrain from redistributing content in the form that the curation platforms offer by default.
To continuer along this path, to despoil the content of authors who give of their time, to steal their traffic is to impoverish that which adds vibrancy to a Web, the authors, some of whom are unpaid.

PS: for those who’d like to accuse me of taking part in this movement, I’ll admit: I tested Scoop.it and paper.li and since publication of this post I am going to delete those accounts. You need to know what you’re talking about.
In addition, I believe I am trying to contribute in my way to the creation of value on the Web and if I assess this by the discussions of the last few days, I tell myself that it’s a course of action from which I should not stray because richness, comment and participation encourage enrichment, sharing and creation. This is of course not true of curation.

Photo credit: http://tribulations-lambda.over-blog.com/article-5454220.html (well, let’s say I found
the photo there…)

Points of the same colour and close to each other represent individuals with similarities (e.g. workplace, business) and/or sharing a set of common contacts. http://inmaps.linkedinlabs.com/network

While we often talk of information glut and seek remedies to reduce or minimise this flow of information, mapping can be an initial feedback element.

Without getting to the crux of the problem – if there really is one – data mapping holds several aces in view of ever-increasing stockpiles and flows of information.

First of all, data mapping structures the information. Mapping can provide an initial level solution, whether this involves clustering the information to “discover” groups of documents, objects which have similarities or even to build up sometimes complex document trees on several levels and which are sometimes interlinked.

Nevertheless, it could be said in essence that these aces are more linked to statistical calculation (one of the examples is text mining to identify salient themes and terms that allow clusters to be built up) or to the use of the metadata of the items observed than to the mapping itself. This is true. A map is always based on data and the more reliable this data is, the more structured and qualified it is, the greater the possibilities offered by mapping this information will be.

However, mapping in itself incorporates various advantages that are linked to visual representation.

• The spatialisation of a world allows more interpretation aspects to be added and the position of each object in relation to others can be used to provide meaning. Some mapping solutions even go as far as to offer three-dimensional displays so as to enable the simultaneous display of a larger number of variables and the relationships they maintain.

• The map display makes an impact. It’s obvious that the adage “a picture is worth a thousand words” also makes sense in a professional world. Ease of storage and communication are elements that can transform the data into information for those who receive it.

• The map can be interactive and provide a means of exploring the dynamic data, enabling time to be saved when reassessing sets of information from another point of view or at another level of depth.

Mapping of people connected with competitive intelligence activities based on the Viadéo network and previously published on Actulligence.

Consequently, mapping is a real boon for those who may manipulate the data, the information. For processing it, for exploring it and for communicating it.

However, the advantages of mapping should not allow its pitfalls to be forgotten. Mapping is in the main only worthwhile for the information whose display it enables. Completely unstructured and incoherent information, a distorted mapping input collection process and meaningless spatialisation algorithms are likewise errors that can turn mapping into a counter-productive tool which could even go so far as to distort the information.

In order that data mapping is indeed a real business tool, it is vital that it is treated seriously and not as a mere visual gadget and that the information collected and the map views are processed and produced by people who understand the operations they’re carrying out and the choices they’re making at each stage and that they likewise understand the impact this will have on the maps that are produced.

At the end of this map building process , it will then be possible to read and analyse this mapping by incorporating the choices made during the creation process and being aware of the de facto limits of the mapping.

What are the main types of mapping you come across in business and what are the difficulties encountered in creating them?

For a start, I would make a distinction between mind mapping and data mapping.

• Mind mapping is a particularly effective work and display tool, but one that has different characteristics from a data mapping tool, which for me would be the following:
• Data mapping must be able to process and display large volumes of data.
• It must also be able to spatialise the data automatically according to this data or the variables of this data or variables resulting from the relationships between the objects.
• Finally, it must provide tools for graphic display and data differentiation (sizes, colours, spacing).

The maps that I come across most in business today are:

Map published in "Die Zeit" representing political parties and their corporate donors.

• Maps linked to the Web and enable working on website networks and facilitate the identification of the relationships between sites around a topic. These maps are particularly effective since they address two obvious problems of volumetric analysis (of sites and pages) and complexity of interactions. The main limits of this type of mapping are based on the upstream extraction of the relationships between sites.
• Human network maps which are based on data either collected and rated “by hand” or on data collected automatically and which provide a point of view of a network of people (e.g. map of emails exchanged or phone calls made, e.g. map of “public” or business social network address books, for example).
• The “market intelligence” maps which are used mainly in Competitive Intelligence or Business Intelligence Departments and enable the mapping of relationships between economic stakeholders, products and markets and the display of the respective sizes of these stakeholders on their markets. They are different from Web-oriented maps since they map a world whose objects are not uniform and can cope with different and more complex relationships than a mere sharing of links. (For example, company X has company Y as a subsidiary which produces the product range A1 and A2 with a volume of 10,000 in country 1 and 350,000 units in country 2 respectively.) They are also different due the complexity of the information to be displayed in one and the same space: people, companies, products, results, turnover figures, market shares, etc.
• Document maps that enable the display of and/or interaction with structured (with metadata and definite fields) or unstructured sets of documents. They can be used in bibliometrics for example, but also for scientific monitoring of sets of patents.

There is nevertheless an infinity of uses for mapping. There is no shortage of data today and it deserves to be processed by mapping.

Finally, here’s some sound reading matter and lines of inquiry on information mapping to finish with.

Softwares for mapping and dataviz :

• Pikko Software which enables the representation of complex bodies/relational data models, and does so in a fairly flexible way, with its Vision Link Desktop and Server tool.
• Touchgraph, more relevant for processing larger but less complex volumes of data. They became known for their Google results mapping (using the related command) and their Facebook address book mapping demonstrators.
• Analyst Notebook, highly prised by official inquiry and investigation organisations. Very powerful and its recent buyout by IBM should enable it to grow. Its only drawback: the complexity of getting used to it and incidentally its price.
• Just Map it!, mapping solution supplied by Social Computing, which has just launched a mapping solution enabling the mapping of RSS feeds and the posting relationships between them means of tags.

• And finally, Gephi! THE open source mapping software. A rather active community is developing and sharing several plug-ins and a solution that is constantly being developed. Cannot be ignored, slightly clunky to get used to, free. One criticism which I want to make about it..: it’s not possible to make the links clickable.

I’ve probably forgotten some. This list is not meant to be exhaustive…#uselessclaims

In the must read group:

• Infosthetics. Absolutely outstanding. Source of inspiration and of thought. Trying to reconcile the pretty with the useful. At any rate Infosthetics gives us imagination and aestheticism. It is your job to see how to apply all these pretty pictures to your business.
• Likewise very good, Visual complexity which makes an inventory of various mapping projects.

The French blog on this topic: Serial Mapper, run by Claude Aschenbrenner. Cannot be ignored.

The book :

Just must be read. And looked at. Data Flow 2 (and Volume 1 too).

The final word: to tell you that mapping tools and algorithms are not an end in themselves. It is your job to you to know what you want to map, to make assumptions, to get usful data for yourself and then to subject it to the scope of your expertise when reading and analysing the data.
And incidentally, if you need a helping hand, this forms part of the sets of projects that Actulligence Consulting has been lucky to be working on for several months now (<= advertising inside. The blogger but above all the businessman in me requires it.)