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World Diabetes Day and dataviz

Strictly speaking, this post is not a post about competitive intelligence, its tools, etc.

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.

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.

[gview file=”https://www.actulligence.com/wp-content/uploads/2012/11/121116-WDD-all_26481.pdf” height=”600″ width=”400″ save=”0″]

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.

[gview file=”https://www.actulligence.com/wp-content/uploads/2012/11/121116-WDD-accounts-sup_5_infinite_network-2844.pdf” height=”600″ width=”400″ save=”0″]

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.

[gview file=”https://www.actulligence.com/wp-content/uploads/2012/11/121116-WDD-hashtags-sup1-1329.pdf” height=”600″ width=”400″ save=”0″]

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:

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.

[gview file=”hhttps://www.actulligence.com/wp-content/uploads/2012/11/121116-WDD-accounts_and_hashtags-modularity_wdd_sup-4291.pdf” height=”600″ width=”400″ save=”0″]

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:

[gview file=”https://www.actulligence.com/wp-content/uploads/2012/11/121116-WDD-accounts_and_hashtags-modularity_wdd_2287.pdf” height=”600″ width=”400″ save=”0″]

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:

Our mapping proposition:

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