The European Commission’s EMPL presence on Twitter in 2012: Trending topics
Identifying the trending topics of the communications managed by the three account holders on Twitter in 2012 started with processing the hashtags’ and extracting their occurrences. Comparing the most used hashtags with word frequency (not hashtags, but ordinary words), word pairs (pairs of words based on their proximity) and semantic network nodes may provide clear indications and relevant elements to identify the trending topics of Twitter communications. Both word pairs and semantic network nodes will be further explained and developed in this article.
Most frequent words with at least 52 occurrences
The list of the most frequent words in the unified tweet corpora of the three account holders, namely Social Europe, EURes and Commissioner Andor in 2012, resulted from a WORDij procedure. The word frequency ranged from 465 to 2. I selected the first ranked 42 words with at least 52 occurrences only as from 52 to the next lowest level was a significant gap. The selected words included most of the hashtags and related words. Usernames, locations and other irrelevant words were discarded. The validated words as well as the discarded words (in grey) are placed in Table 1.
The most frequent word pairs
WORDij also extracts word pairs based on an algorithm that uses the rule of word proximity. The application placed 1934 word pairs in output, but I selected the top 32 word pairs. Their proximity makes sense in the context of the Twitter communications of the three account holders and relates well to the hashtag set and the most frequent words (Table 2).
According to Danowski and Park (2013) the “order of words within pairs” is “maintained so that a pair (word A – word B)” is treated as a distinct entity from (word B – word A) (p.24).
Twitter semantic networks
Extracting the semantic network nodes with WORDij provided additional information to be triangulated with the other datasets to ensure that key information is not left out. Given some limitations of LIWC (the other piece of CAQDAS tool, which I used), I wanted there to be in place a “human” filter to ensure research credibility.
I created a set of spring-embedded graphs to check how the semantic entities grow from 5 to 30 nodes. The graphs show the gradual growth from the strongest 5 nodes to the following 5, 10 and 20 which enrich the network.
The semantic networks of the three account holders, based on the unified tweet corpora, with 5 and 30 network nodes are presented in Figure 1 and Figure 2.
The semantic network nodes were analysed and compared against the hashtags, the most frequent words and word pairs. The relevant nodes which are also hashtags are found in Table 3 (#). The discarded nodes are greyed. All nodes (Table 3) are listed in reverse order to show that the strongest nodes are placed at the bottom, which may symbolise a foundation on which the semantic network is built.
Hashtags vs. word frequency and word pairs
Hashtagging was somewhat applied inconsistently and the existing hashtags could not provide a clear and complete picture of the communication trending topics managed by the three account holders. Hashtagging was performed more accurately by Social Europe and the Commissioner. Often no hashtag or multiple hashtags were assigned to one event or policy.
For example, European Job Day (#EJD) and European Online Job Day (#EOJD) were also tagged as #Job, #Jobs, #onlinejobday, #onlinejobsday, #EuropeanJobDay, #EuropeanJobDays, #EuropeanJobsDay, #jobfair. This was also the case with the Youth Employment Package (#EmplPackage, #Employment package, #EmploymentPackage and #YouthEmploymentPackage).
There were also two similar hashtags: “#poverty” and “#poverty12” which were assigned to different subjects. The first was associated to the 11th European Meeting of People Experiencing Poverty (Homelessness and Housing Rights in the Context of the Crisis) while the second was associated to the Second Annual Convention of the platform against poverty and social exclusion, which is a long-term future strategy of the European Union.
Correlating the four information sets ensured that key and relevant information is elicited in order to get an accurate picture of the communication trending topics managed by the three account holders on Twitter in 2012.
Based on the information I extracted from the individual and unified tweet corpora, I established a list of words, which I searched for in each individual tweet body.
The trending topics I identified are listed along with the words I checked for by searching in the corpora. While checking each tweet body to place it into the right trending topic, I considered it as only one occurrence even though the tweet body might have had one or more hashtags, one or more word pairs or semantic nodes covering the same topic. The topics are ranked according to the occurrences of the content entities. A content entity is represented by either one of the following: a hashtag, a word pair or a semantic node.
- Current EU social policies and programmes (607 content entities) including labour market, social dialogue, social investment, social security, Eurofound, #crisis, market, #social, conference, policy;
- European Job Day and European Online Job Day: ( 596 content entities) including #EJD, EJD, #EOJD, EOJD, #job/#jobs, job/jobs, day;
- Youth Employment Package: (447 content entities) including #youth, #employment/#unemployment, package;
- 2012 European Year for active ageing and solidarity between generations (EY2012): (358 content entities) including #ey2012, year, #active #ageing, #solidarity, #generations, awards;
- Jobs for Europe: (252 content entities) including #jobs4europe and jobs4europe;
- Poverty Convention: (87 content entities) including #poverty12;
- Youth Employment chat hosted by Commissioner Andor: (66 content entities) including #youthempl and chat;
- Youth Guarantee: (28 content entities) including #youthguarantee, guarantee.
Trending topics number 3 and 8 are two new political initiatives launched in 2012 and, if approved, would be implemented as EU policies and programmes in the forthcoming years.
Trending topic number 6 covers a major long-term initiative which forms part of the Europe 2020 strategy and is currently implemented in the EU. It is a major political priority to overcome the effects of the crisis, such as poverty and social exclusion. These trending topics have got political weight and represent strategic points for the further development of the EU.
Trending topic number 7 is the Youth Employment chat hosted by Commissioner Andor in which he discussed the Youth Employment Package and Youth Guarantee with young people.
The three tweet corpora were placed into individual monthly files for convenience in searching and finding the time references. The related hashtags, nodes and word pairs were counted according to the topic they belonged to. After manual counting, the figures corresponding to the occurrences were placed in a separate spreadsheet. When this work was completed, I grouped all the entries of the three accounts in a single table, which generated the chart in Figure 3.
The eight trending topics cover the core communication content which was planned for distribution via Twitter. The topics were confirmed by the account administrators in the interviews. The topics formed part of the communication priorities of the European Commission in responding to the crisis on the one hand, and on the other they were in line with the Europe 2020 Strategy (the EU’s growth strategy for the current decade). The topics reflect most of the employment, social affairs and inclusion policies, with a special focus on the generic theme of the 2012 European Year for Active Ageing and Solidarity between Generations (EY2012). It is worth noting the complexity of the policy content and the professional skills of the communicators in making accessible such content to different target audiences. The topics, as ranked earlier, illustrate different communication approaches, from traditional content distribution (featuring official texts) to an online dialogue (Twitter chat) hosted by the Commissioner himself. Therefore, Commissioner Andor and his team together with the other operational accounts’ administrators tried to sustain a genuine two-way communication to ensure openness and willingness to listen to people’s voices and needs.
The European Commission’s role is to propose legislation and in this context the creation of the Youth Employment Package was also based on both official and public contributions. The online dialogue (Twitter chat) is just an example of the Commissioner’s willingness to value the input of people.
A common dimension of the trending topics consists of a set of tailored measures to help people overcome the effects of the crisis: increasing social dialogue, ensuring social security, finding a job, helping young people gain employment, relying on top level key policy makers to identify suitable solutions to the crisis etc. Both the Youth Employment Package and Youth Guarantee are being implemented and the effects will be soon visible, according to the Commission’s official reports.
More information to come in the next articles.
Previous articles on the same subject
 Danowski, J.A., and Park, D.W. (2013), Celebrities in the mass and internet media and social network structures: A comparison with public intellectuals. Manuscript. Chicago, IL: University of Illinois at Chicago