Visualisation of #EURegionsWeek 2017 on Twitter
The European Week of Regions and Cities gathered almost 6000 participants from all over Europe in Brussels on 9-12 October 2017 to investigate how regions and cities can work for a better future in Europe. Participants posted on social networks their take-away and opinions, and commented what happened in the hundreds of workshops, visits, and networking events on the agenda. What follows is my attempt to visualise all exchanges that took place on Twitter during the week of the event.
The graph shows how Twitter accounts are interconnected, indicating who is retweeting and citing who. Twitter accounts are grouped in sub-communities (see below). The size of the dots indicates the number of connections or interactions with other accounts (Weighted Degree). The thickness of the lines indicates the importance of these exchanges between two Twitter accounts.
A total of 10265 tweets where posted on Twitter during the conference's week from Sunday 8 October to Saturday 14 October. The graph visualises the 3727 Twitter accounts (dots) who have tweeted and their 5434 interactions (lines).
Why only on Twitter? Was there no activity on facebook or other social media?
Sub-communities
Sub-communities show how Twitter accounts are grouped together and how often they have tweeted about each other or have retweeted each other. Each member of a sub-community has the same colour circle. The modularity analysis identified more than 300 sub-communities. There are 14 large sub-communities each with more than 100 members. All together, these 14 "big" ones contain half (55%) of all Twitter accounts displayed in the graph. Sub-communities with more than 10 members are 27 and together contain 85% of all Twitter accounts.
The following animation and table show you the 10 most populated sub-communities and, for each, the Twitter account with the most interactions (Weighted Degree).
| Community | Members | Twitter account | Weighted Degree |
|---|---|---|---|
| 1 | 356 | @EU_Regional | 879 |
| 2 | 321 | @albawhitewolf | 448 |
| 3 | 271 | @CoR_President | 169 |
| 4 | 195 | @regstud | 204 |
| 5 | 194 | @PerceiveProject | 75 |
| 6 | 171 | @CCRECEMR | 183 |
| 7 | 158 | @EU_Eurostat | 188 |
| 8 | 133 | @EU_ENV | 46 |
| 9 | 131 | @interregeurope | 109 |
| 10 | 130 | @twente | 92 |
Influencers
So, how to determine who were the influencers during the #EURegionsWeek?
My way of doing is to multiply the visibility of a Twitter account (its Ranking) by its number of interactions in the context of the #EURegionsWeek (its Weighted Degree). The result, available in the "Influence" column, is a measure of the influence a Twitter account may have had during the #EURegionsWeek period.
The table is sorted in descending order of "Influence". Feel free to sort the columns in another order by clicking the header of a column.
| Twitter account | Weighted Degree | Ranking | Influence |
|---|---|---|---|
| @EU_Regional | 879 | 9 | 7911 |
| @albawhitewolf | 448 | 6 | 2688 |
| @EU_Eurostat | 188 | 10 | 1880 |
| @INTERREGTweets | 163 | 8 | 1304 |
| @EU_CoR | 156 | 8 | 1248 |
| @regstud | 204 | 6 | 1224 |
| @CCRECEMR | 183 | 6 | 1098 |
| @WolfgangPetzold | 203 | 5 | 1015 |
| @CoR_President | 169 | 6 | 1014 |
| @EU_ScienceHub | 98 | 8 | 784 |
| @CocoDeBrux | 141 | 5 | 705 |
| @europeanregions | 134 | 5 | 670 |
| @interregeurope | 109 | 6 | 654 |
| @CorinaCretuEU | 77 | 8 | 616 |
| @100ResCities | 62 | 9 | 558 |
| @twente | 92 | 6 | 552 |
| @cohesify | 137 | 4 | 548 |
| @EU_eHealth | 66 | 8 | 528 |
| @EPP_CoR | 105 | 5 | 525 |
| @UNHABITAT | 57 | 9 | 513 |
| @LvNistelrooij | 73 | 7 | 511 |
| @captain_europe | 100 | 5 | 500 |
| @RegioEvaluation | 104 | 4 | 416 |
| @DigitalSkillsEU | 52 | 8 | 416 |
| @EP_ThinkTank | 52 | 8 | 416 |
| @citizenlabco | 59 | 7 | 413 |
| @EU_ENV | 46 | 8 | 368 |
| @FEANTSA | 52 | 7 | 364 |
| @SallyJHardy | 90 | 4 | 360 |
| @stracma | 60 | 6 | 360 |
| @saved_mat | 89 | 4 | 356 |
| @PES_CoR | 59 | 6 | 354 |
| @icalzada | 67 | 5 | 335 |
| @PorCalabria | 66 | 5 | 330 |
| @ktowens | 47 | 7 | 329 |
| @ESEC2 | 82 | 4 | 328 |
| @EUEnvironment | 35 | 9 | 315 |
| @ansaeuropa | 39 | 8 | 312 |
| @DSMeu | 34 | 9 | 306 |
| @gazzema | 43 | 7 | 301 |
| @EJAAriza93 | 97 | 3 | 291 |
| @EU_Commission | 29 | 10 | 290 |
| @MSCActions | 40 | 7 | 280 |
| @europainitalia | 31 | 9 | 279 |
| @AgnesMONFRET | 53 | 5 | 265 |
| @CllrLawrie | 61 | 4 | 244 |
| @Parlimag | 30 | 8 | 240 |
| @InteractEU | 46 | 5 | 230 |
| @jihan65 | 45 | 5 | 225 |
The "Weighted Degree" is the number of interactions in the context of the #EURegionsWeek for a Twitter account, but weighted by the weigtht of each interaction. The size of the dots in the graph is proportional to the "Weighted Degree" value. The bigger the point, the more interactions the Twitter account has had with others during the #EURegionsWeek period. ("Weighted Degree" is calculated by the Gephi tool)
The "Ranking" indicates the overall visibility of the Twitter account, based on its number of followers and lists, values range from 1 to 10. The Twitter account's visibility is independent of its activity during the #EURegionsWeek period. The higher the value, the more visibility the Twitter account has and the more it may reach and influence others on Twitter. ("Ranking" is calculated by the Digimind tool)
Interested to know more about the methodology and the used tools? I provide more details in the following page.