Political personalization on Facebook and Twitter.
How personalized are social media posts of MEPs of Poland, Ireland and Germany?
Magdalena Skrzypek Student number 10831703
Master’s Thesis
Erasmus Mundus Master's in Journalism, Media and Globalisation University of Amsterdam, Graduate School of Communication
Supervised by Sanne Kruikemeier 26 June 2015
Abstract
A growing amount of literature points to increasing personalization in political communication, with social media serving as a channel for creating more personal and direct interactions with voters. By employing a content analysis of social media posts, present research investigated differences in the presence and types of personalization in the social media content of Members of European Parliament during their routine period of work. The findings show that different dimensions of personalization, including individualization, emotionalization and privatization are employed to a different extent. A comparison between two platforms shows that personalized communication is more often used on Facebook than on Twitter. The study also examines three different countries – Poland, Germany and Ireland and explores individual-level variation. Consequently, MEP’s demographic characteristics, such as age, gender, political affiliation, incumbency and their engagement in the work of Parliament are taken into consideration. In this regard, the findings show differences between Poland and Germany, with Ireland lying in between them. However, the study shows that variation in the levels of personalization cannot be attributed to the abovementioned demographic and individual characteristics of MEPs, with only gender approaching significance. It can therefore be concluded that other explanatory variables must be sought elsewhere.
Keywords: MEPs, European Union, social media, Facebook, Twitter, content
Introduction
Despite the increasing influence of the European Parliament, the institution still suffers from the democratic and communication deficit, failing to stimulate public debate and media coverage (Meyer 1999; Anderson & McLeod 2004; Martins, Lecheler & de Vreese, 2012). The gap between the public and the European governance has been growing (Boomgaarden et al., 2013), as the further decrease in voters’ turnout during the 2014 European Parliament elections demonstrates. In light of this, several scholars and policy makers have been advocating for the application of new technology and implementation of e-governance in the democratizing process of the EU (Engström, 2002; European Commission, 2007; Michailidou, 2008). Such e-representation could be valuable for Members of the European Parliament (MEPs), due to their geographical remoteness from their home parties and constituents (Lusoli, 2005), allowing them to connect to those they represent.
Specifically, social media are online platforms that facilitate possibilities for engaging with the public. They allow for horizontal and vertical communication between political actors and citizens without the interference of journalists (Kruikemeier, 2014a). They also provide a hybrid space, where the traditional distinctions between private and public are blurred (Enli & Thumin, 2012). As stated by Enli and Skogerbø (2013), “social media, like Facebook and Twitter, place the focus on the individual politician rather than the political party, thereby expanding the political arena for increased personalized campaigning” (p. 757).
The present study adds to the growing discussion on personalization, generally understood as a shift of focus from parties and institutions to individual politicians and
leaders (Van Aelst, Sheafer & Stanyer, 2011). It focuses on Facebook and Twitter, due their potential for profiling and self-promotion and increased popularity among voters (Kruikemeier, 2014a). By employing an extensive content analysis of tweets and Facebook posts, it aims to explore differences in the presence and types of personalization on social media of the Members of the European Parliament from Germany, Poland and Ireland. It amends and expands existing theoretical considerations and past empirical work in four ways. First, the research combines different operationalizations of the personalization, identifying different approaches throughout academia, clarifying the concept and creating a comprehensive model for the analysis. The study concentrates on three dimensions of personalization – individualization, privatization, and emotionalization (Kruikemeier, 2014a). Consequently, it explores contents about individual competences, professional activities, private lives and emotional reflections (Van Santen & Van Zoonen, 2010, Kruikemeier, 2014a). Second, unlike most of the scholarly work on social media and the European Union centering on campaign periods and exogenous events (e.g. Vergeer, Hermans & Sams, 2011a; Obholzer, 2015), the study analyses a routine period, in which “no significant EU events took place” (Boomgaarden, Vliegenthart, de Vreese & Schuck, 2010, p. 509). It provides a new insight into everyday MEPs' social media presence, adding to the limited research on social media use in permanent campaigning and the day-to-day online activities of politicians. Third, in their studies, researchers of online political communication have concentrated their attention overwhelmingly on one channel of communication – the politician or party’s website (Schweitzer, 2005, 2008; Kruikemeier, van Noort, Vliegenthart & de Vreese, 2013), Twitter (Otterbacher, Shapiro & Hemphill, 2012; Kruikemeier, 2014b, Larsson, 2014,) or Facebook (Andersen & Medaglia, 2009; Larsson & Kalsnes, 2014). The
prevalence of personalized content in the context of European Parliament has so far been limited to investigation of candidates’ or MEP’s websites (van Os, Hagemann, Voerman & Jankowski, 2007; Lilleker & Koc-Michalska, 2013; Hermans, Vergeer, 2012). This study, however, offers a comparison of Twitter and Facebook, “two of the most popular and recognizable social networking tools on the internet” (Tagtmeier, 2010, p. 8), and thus sheds new light on the differences in the presence and types of personalization between the two networks. Fourth, apart from offering a comparison between the networks, the research examines individual-level variation and the differences between three countries. The study draws on three cases with dissimilarities on the country-level, namely Poland, Germany and Ireland, which allows for “demonstrating the robustness of an association between dependent and explanatory variables” on an individual level (Van de Heijden, 2014). MEP’s demographic characteristics, such as gender and age are included. Incumbency status is incorporated in order to examine whether it is relevant for the variation in the levels of personalization. Political affiliation of MEPs is also considered as one of the explanatory variables. The study also introduces previously unreported variable, mainly MEPs’ participation in roll-call extracted from VoteWatch Europe (2015), to test if the level of engagement explains the differences in the levels of personalization. Taking the abovementioned into account, three main research questions are formulated:
RQ1: To what extent do MEPs from Poland, Germany and Ireland use personalization, i.e., individualization, privatization and emotionalization, in their communication on Twitter and Facebook?
RQ2: To what extent do the levels and types of personalization, i.e., individualization, privatization and emotionalization, used by MEPs differ in Poland, Germany, and Ireland?
RQ3: To what extent does gender, age, incumbency status, political affiliation and MEPs’ engagement and country of origin explain the level of political personalization?
Theoretical framework
Scholars offer different definitions of personalization and consequently, various operationalizations of personalization have been distinguished within the literature (Langer 2007; Rahat & Sheafer, 2007; Van Santen & Van Zoonen, 2011; Van Aelst, Sheafer & Stanyer, 2011). In general, personalization entails the change of focus from parties and organizations to candidates and leaders (Van Aelst, Sheafer & Stanyer, 2011) and from professional competences to features related to non-political personality traits (Kriesi, 2011). It should be emphasized, however, that lack of consensus in the theoretical understanding of the notion hinders the coherence of the existing research, with a mixed empirical evidence (Kriesi, 2011; Karvonen 2010). Some studies find evidence for increased personalization within political communication (Mughan, 2000; McAllister, 2007, Rahat & Sheafer, 2007; Langer 2007) and some do not (Kaase, 1994; Schulz, Zeh & Quiring, 2005; Adam & Maier, 2010). Researchers also point to different consequences of the phenomena. Personalization is said to influence voters’ behaviour (Kleinnijenhuis, Maurer, Kepplinger, & Oegema, 2001; Garzia, 2011) and evaluations of the candidates (Druckman, 2003; Garzia, 2011), but also to contribute to political cynicism (Jebril, Albaek & de Vreese, 2013). In his overview, Brettschneider (2008) concludes that personalization might be seen as leading both to depoliticization and increased effectiveness of messages, as it gives parties a face and a voice.
In this respect, there seems to be more agreement about the connection between personalization and social media (Enli & Skogerbø, 2013; Kruikemeier, van Noort,
Vliegenthart & de Vreese, 2013; Vesnic-Alujevic, 2013; Kruikemeier, 2014a). It is agreed that personally kept platforms, such as Facebook or Twitter add to the personalization of politics, placing the emphasis on the individual politician rather than on the political party thereby blurring the borders between the private and public spheres (Enli & Skogerbø, 2013). Social media offers opportunities for individual politicians to profile themselves and facilitate direct communication with citizens (Kruikemeier, van Noort, Vliegenthart & de Vreese, 2013). Still, research on the effects of personalization within social media is inconclusive, indicating that on the one hand personalization enhances message recognition and recall (Lee & Oh, 2012) and increases political involvement and a feeling of closeness (Kruikemeier, van Noort, Vliegenthart & de Vreese, 2013). On the other hand, however, some studies also discover no effect of personalization on the electoral support (Kruikemeier, 2014b) or that personalization actually predicts a campaign loss (Parmelee & Bichard, 2011).
Existing research also does not provide one unified typology of political personalization. However, there seems to be a consensus that personalization is a multidimensional phenomenon (Van Aelst, Sheafer & Stanyer, 2011; Van Santen & Van Zoonen, 2011; Holtz-Bacha, Langer & Merkle, 2014). Consequently, three dimensions of personalization, based on previous research are sought within the present study. Following Van Aelst, Sheafer and Stanyer (2011) and Van Santen and Van Zoonen (2010), attention is aimed on “individualization” defined as “focus on individual politicians as central actors in the political arena, including their ideas, capacities and policies“ (Van Aelst, Sheafer & Stanyer, 2011, p. 204). Then, the study examines “privatization”, which encompasses “focus on private persona of politicians” (Van Santen & Van Zoonen, 2011, p. 14), namely their
private lives and features derived from the private sphere (Langer, 2007). The last dimension of personalization that is being explored is “emotionalization”, understood as “focus on personal experiences and emotions of politicians” (Van Santen & Van Zoonen, 2011, p. 14).
Previous scholarly work enables us to hypothesise that the way politicians use their social media and consequently employ personalization might differ (e.g. Giebler & Wüst, 2011; Larsson, 2014). Based on the unique characteristics of Facebook and Twitter (Elmer, Langlois & McKelvey, 2012), it can be speculated that the levels of personalization would vary between the networks. As suggested by Syn and Oh (2015), Facebook mainly encourages establishing personal relationships and online communities, while Twitter serves as a microblogging platform “through which users publish short comments or messages within individual, group or public networks” (p. 2). Moreover, in their research on the usage of social media in Norwegian election campaigns, for example, Enli and Skogerbø (2013) found that Norwegian politicians distinguished clearly between Facebook and Twitter, pointing to Facebook as intimate and to Twitter as a marketing platform. Another major difference between Facebook and Twitter is the post size – while Facebook posts can be pages long, Tweets allow only 140 characters. Twitter’s brevity prompts the use of abbreviations and symbols as well as simplified sentence structure, which make the information more concise (Zhao & Rosson, 2009). Consequently, it also leaves little space for a personalized style of language. For the abovementioned reasons, the first hypothesis assumes that on the whole personalization will be higher on Facebook.
H1: MEPs use of personalized communication will be higher on Facebook than on Twitter.
Furthermore, it could be expected that MEPs from left and right wing political parties might differ in their use of personalization on social media. For example, the degree of
professionalization is found to be higher among conservative parties (Giebler and Wüst, 2011). Gibson and Rommele (2009) also argue that parties with left wing or more socialist agendas are less inclined to adopt business-like practices, such as formal marketing or use of outside consultancy, compared to right-wing parties. Additionally, multiple scholars found positive association between openness and left-wing ideology (Thorisdottir, Jost, Liviatan & Shrout, 2007; Roets & Van Hiel, 2009; Roets, Cornelis & Van Hiel, 2013). Hence, it might be hypothesised that candidates from left-wing political groups would be less formal and more frequently employ a personal style of communication. Accordingly, the next hypothesis proposes:
H2: The levels of personalization used on social media by the MEPs of left wing parties will be higher than by the MEPs from right wing parties.
It is also expected that politicians’ age may affect the use of personalization. The bulk of scholarly research indicates that a younger age is a significant factor behind the use and adoption of social media among politicians (Chi & Yang, 2010; Carlson & Strandberg, 2008). Giebler and Wüst (2011) found, for example, that older candidates for European Parliament use less post-modern campaigning tools, including personal websites, social media or e-mail marketing. Additionally, Lilleker and Koc-Michalska (2013) claim that younger MEPs more often personalize their online spaces. In their study on facebook usage, Nosko, Wood and Molema (2010) also found that disclosure of information, in particular sensitive personal information, decreases with the progression of age. They state that young people feel more comfortable with online disclosure and the revealing of certain types of information may not be seen as appropriate with the increase of age (Nosko, Wood and Molema, 2010). As a consequence, it is hypothesised that younger MEPs are likely to be
more social media-savvy but also more willingly share personal information. In view of the aforementioned fact, the third hypothesis is formulated:
H3: The levels of personalization used on social media by younger MEPs will be higher than by older MEPs.
Moreover, the gender of the candidate should be taken into account, as “women’s perceptions, meanings, experiences – including their communicative experiences – are different from men’s” (Foss & Foss, 1991, p. 21). Males and females have different communication styles, with existing scholarly work asserting that males use more formal and informational words and focus more on impersonal topics, whereas females employ more social interaction and emotionally intensive words (Argamon, Koppel, Fine & Shimoni, 2003; Newman, Groom, Handelman & Pennebaker, 2008; Mukherjee, Liu, 2010). Moreover, Dow and Tonn (1993) claim that feminine style of political communication “uses personal experience, anecdotes and examples as evidence, exhibits inductive structure, emphasizes audience participation, and encourages identification between speaker and audience” (p. 287). Parry-Giles and Parry-Giles (1996) also add that it is more personal, intimate, emotional and self-disclosing. As a result, it seems plausible to hypothesise that women might employ more personalization on their social media than man. It is therefore claimed:
H4: The levels of personalization used on social media by female MEPs will be higher than by male MEPs.
Lastly, the length of service of Members of European Parliament is considered. Following the findings of Lilleker and Koc-Michalska (2013), which point to the fact that MEPs sitting in the parliament for the first term are the most likely to personalize their online spaces, the last hypothesis implies as follows:
H5: The levels of personalization used on social media by MEPs with shorter length of incumbency will be higher than by those holding office for longer periods.
Methods Sample and data collection
To empirically test the hypotheses and investigate the research questions quantitative content analysis is used. The quantitative method is more appropriate for the substantial size of the sample to be considered, but at the same time might limit in-depth analysis. Still, the statistical nature allows for generalization, while objectivity is increased by collection of numerical data. Absence of bias is further strengthened by the use of content analysis, which according to Berelson (1952) “is a research technique for the objective, systematic, and quantitative description of the manifest content of communication” (p. 18). In addition, the content analysis excludes major ethical issues, due to unobtrusiveness, lack of human subjects and collection of already existing data available to everyone (Berelson, 1952).
The study also draws on three cases with dissimilarities on the country-level, namely Poland, Germany and Ireland, and explores the individual-level variation among Members of the European Parliament. The data contains the social media activities of 158 MEPs – 96 from Germany, 51 from Poland and 11 from Ireland. The selection of countries follows the principle of a most different system design (see Table 1). Two institutional features such as voting system as well as political and media system (Hallin and Mancini, 2004) are considered. Variables on a European level, such years of accession and number of MEPs are also included. Since the study concerns social media, Internet-related characteristics are also accounted for.
Table 1. Country characteristics
Poland Ireland Germany
Voting system
Preferential voting
Single
transferable vote Closed lists Political and media system (Hallin &
Mancini, 2004) Post-communist Liberal model
Democratic corporatist
Year of EU accession 2004 1973 1952
Number of MEPs 51 11 96
Daily users of internet (Eurostat, 2014a) 51% 65% 72%
Households with internet access
(Eurostat, 2014b) 75% 82% 89%
In this paper, a content analysis is used and the unit of analysis is a single tweet or Facebook message. As not all MEPs maintain social media, only those available are analysed. To establish the list of candidate’s accounts, information available at the European Parliament website (2015) or at personal websites of MEPs is used. For Facebook, both fanpages and private accounts with open access and the “follow” option are considered for analysis. If the candidate has both, only the fan page is examined to ensure that information was intended for citizens rather than the close group of friends. Only accounts with more than 5 tweets and 5 posts published after 25 May 2014, the last day of European Parliament elections, are considered in order to control for campaign effects. Additionally, accounts of two polish MEPs, Andrzej Duda and Janusz Korwin-Mikke, are excluded, due to their running for the Polish presidential elections.
Consequently, 104 Twitter accounts and 143 Facebook accounts are examined. Five last Tweets and Facebook posts of each MEP are collected on 15 Mach, 2015 using the data collection program “Facepager“ and inserted into an Excel spreadsheed. Only original content is reviewed, with retweets and shares being discarded. Photos and videos are not
included in the analysis, due to focus on written rather than visual content. As a result, content of 1235 posts, including 520 Tweets and 715 Facebook posts are analysed.
Coding procedure and measures
The present study applies a deductive approach, with categories and a coding scheme derived from previous studies and theories (Van Santen & Van Zoonen, 2010; Van Aelst, Sheafer & Stanyer, 2011, Hermans & Vergeer, 2012; Kruikemeier 2014a). Several dimensions of personalization are treated as the dependent variables. Individualization, which encompasses “focus on individual politicians as central actors in the political arena ̈ (Van Aelst, Sheafer & Stanyer, 2011, p. 204), denotes content on MEPs’ career that contains references to their professional qualities, professional activities, political achievements or description of political career (Van Santen & Van Zoonen, 2010; Hermans & Vergeer, 2012; Kruikemeier 2014a). Privatization, defined as “focus on private persona of politicians” (Van Santen & Van Zoonen, 2011, p. 14), indicates content concerning MEPs’ private life, such as information on family relationships, love life, domestic life, religious belief, leisure time, personal interests, hobbies, vacations and biographical details. Emotionalization, understood as “focus on personal experiences and emotions of politicians” (Van Santen & Van Zoonen, 2011, p. 14), describes whether MEPs express their emotions within the coding unit. In the case of emotionally charged content, the reflected emotion is classified as positive, negative, or other (mixed/ balanced/ ambiguous). The feelings have to be manifested clearly and the analysed content needs to contain words or phrases that have references to a specific type of emotional experience or state. Following Danner, Snowdon and Friesen (2001) coders are instructed to code only “words that in context described the emotion that was experienced and behaviours subsequent to emotional arousal” (p. 806). Descriptions of possible elicitors
of emotion are not coded.
The present study aims at exploring the degree of correlation between the dependent variables and the independent variables. The first independent variable included is the political affiliation of MEPs. The political groups are divided alongside political spectrum of the left-right divide, with right-wing Europe of the Freedom and Direct Democracy Group and European Conservatives and Reformists, center-right Group of the European People's Party, centrist Alliance of Liberals and Democrats for Europe, center-left Group of the Progressive Alliance of Socialists and Democrats in the European Parliament and left-wing The Greens/European Free Alliance and European United Left/Nordic Green Left (Ginsberg, 2010; Olper, 2014). The non-attached Members were evaluated based on their party affiliation in their home countries prior to elections. One German MEP, Martin Sonneborn, has no political ideology defined, as his satirical political party Die PARTEI cannot be placed into a traditional left–right dimension. Demographic variables are also introduced, including age and gender as well as the length of the service. Using data from VoteWatch Europe (2015), participation in roll-call votes is also accounted for to test whether more active MEPs use a more personalized style. Additionally, the country of origin of the MEP as well as topic and focus of the social media content are coded for.
The aforementioned categories and measures are included in the codebook developed a priori (see Appendix). While devising the codebook, it is ensured that categories are exclusive and that clear instructions are provided to increase the accuracy of the measures and decrease subjective interpretations (Bryman, 2012, p. 303). The main coding procedure involves investigation of the analysed social media content. Data is collected in a nominal scale, by using numbers that represent a category to which a unit of analysis belongs. To
identify types of personalization, a binary coding strategy is employed, as the length of a Tweet leaves no room for measuring intensity. Following Van Aelst, Sheafer and Stanyer’s suggestion (2011), the codebook is based on dichotomous categories, which questioned whether a specific indicator is present or not within the unit of analysis. Consequently, the presence (1) or absence (0) of each type of personalization in material is coded. For each unit one or more types of personalization could be identified. The data is entered into a Microsoft Excel spreadsheet, which acts as a code sheet.
One graduate student, trained in quantitative content analysis and fluent in the languages in which the content is written, codes all the data. To increase reliability, the coding process is implemented after a series of training sessions. In addition, to determine intercoder reliability, a second coder analyses 10% of the complete dataset (123 social media posts).
Table 2. Intercoder reliability estimates
Kalpha Percent agreement
Topic Focus Privatization Emotionalization Type of emotions
Individualization (professional qualities) Individualization (professional activities)
Depersonalization 0.609 0.61 0.854 0.867 0.836 0* 0.809 0.671 65% 72.4% 99.2% 97.6% 96.7% 99.2% 91.1% 88.6% N = 123
* Individualization encompassing professional qualities is almost undetectable. Consequently, low Kalpha may be caused by the skewed data.
Results
In response to RQ1, the findings show that different dimensions of personalization are employed to different extents (see Table 3). Individualization encompassing content on professional activities is the most often used (40.3 per cent). Emotionalization is not much utilised (11.4 per cent), but a clear dominance of positive emotions can be traced if emotions are displayed (85.1 per cent). Negative emotions (12.8 per cent) and those neutral, mixed or ambiguous (2.1 per cent) are rarely expressed. Additionally, MEPs hardly ever disclose information about their private life, which is reflected in the low levels of privatization (3.7 per cent). Individualization dealing with professional qualities is the least employed among the dimensions (1.8 per cent). It should be mentioned, however, that almost half of the analysed social media messages does not reveal any traces of personalization (49.2 per cent).
Table 3. Mean score on dimensions of personalization
Mean SD
Privatization Emotionalization
Individualization (professional qualities) Individualization (professional activities)
Depersonalization .04 .11 .02 .40 .49 .19 .32 .13 .49 .50 N = 1235
To provide a broader overview, additional analyses are conducted. Some of the dimensions of personalization appear more frequently in retaliation to certain topics. Emotionalization and privatization are particularly visible in posts on sports, with more than half of sports-related messages filled with emotions of politicians (54.5 per cent) and information concerning MEPs’ private life (63.6 per cent). Moreover, traces of individualization were found in majority of posts in the topic category of professional
working activities (86.9 per cent). On the whole, depersonalised and personalised content was spread rather evenly across different topics (see Figure 1), with the few exceptions in the topic categories of protests (62.5 per cent of protests-related posts personalised), education (63.6 per cent of education-related posts personalised), health (73.3 per cent of health-related posts personalised), sport (81.8 per cent of sport-related posts personalised) and professional working activities (89.1 per cent of posts personalised).
Figure 1. Personalised and depersonalised content across different topics
0 50 100 150 200 250 300 Personalised Depersonalised
Regarding RQ2, there is a significant difference in depersonalization levels between the three countries (χ2 = 6.73, p = .035, df = 2, V = .07). However, only the difference between Poland and Germany is significant in this data set, with 55.1 per cent of posts of Polish MEPs and 47.8 per cent of posts of German MEPs personalized. With 53.8 per cent of posts personalized, Ireland lies in between and is neither significantly different from Poland nor from Germany. The differences between specific dimensions of personalization – emotionalization, individualization and privatization – were not significant (p > .05).
In order to answer RQ3 and test the previously stated hypothesis, a series of crosstabulations was performed. With regard to H1, the level of personalization within MEPs’ content was indeed higher on Facebook (58.3 per cent of posts personalised) than on Twitter (52.7 per cent personalised), with a significant difference in personalization levels between the networks (χ2 = 29.36, p = .001, df = 1, V = .15). Differences between specific dimensions, including emotionalization (χ2 = 4.24, p = .039, df = 1, V = .06), individualization of professional qualities (χ2 = 10.02, p = .002, df = 1, V = .09) and individualization of professional activities (χ2 = 39.78, p = .001, df = 1, V = .18) were also detected between Twitter and Facebook. Only privatization showed no statistical significance (χ2 = .25, p >.05, df = 1, V = .14), as far as variation between two social networks is concerned.
Moreover, findings show that there are no particular differences in the levels of personalization between MEPs from left and MEPs from right wing parties (p = .320), older and younger MEPs (p = .671) and MEPs with shorter and longer lengths of incumbency (p = .562). In all abovementioned cases variation in general levels of personalization and specific dimensions of personalization is not significant (p > .05). The chi-square test also does not
show any significant difference related to the levels of participation of the MEPs (p = .570). Based on these results, hypotheses H2, H3 and H5 seem to be refuted. The difference between female and male MEPs is reaching significance (p = .062), however variance between specific dimensions of personalization is also insignificant (p > .05). Because the evidence provided is not strong, H4 should be interpreted with caution.
Table 4. Crosstabulation of personalization and gender
Personalization Gender χ2 V Females Males Yes 54.4% (236) 48.8% (391) 3.48 .06 No 45.6% (198) 51.2% (410) Total 100% (434) 100% (801) N = 1235 Note: * p <.05. ** p <.01. *** p <.001
Lastly, a logistic regression was performed to ascertain the effects of gender, age, incumbency status, political affiliation, level of engagement and MEPs country of origin on the likelihood of utilization of personalization (see Table 4). The abovementioned independent variables were included in the model. The results indicated that regression was not significant (χ2 = 16.54, p = .089, df = 9). The strength of the prediction was very low – around 2% of the variation in frequency of personalization could be predicted on the basis of the independent variables (R2 = .02). Incumbency, participation, political affiliation and country of origin have very weak association with frequency of personalization (p > .05). The only association that approached significance was age (p = .071) and gender (p = .072).
Table 5. Predictors for the occurrence of personalization
Personalization of social media content
Predictor B S.E. OR
Age Incumbency Participation Gender (ref. = male) Affiliation Left Right Country Poland Germany Ireland -.107 .068 .022 .225 .354 .372 -.409 .017 -.311 .060 .048 .024 .126 .284 .292 .328 .325 .358 .899 1.071 1.022 1.251 1.425 1.450 .664 1.017 .732 Note: * p <.05. ** p <.01. *** p <.001
Conclusion and discussion
The purpose of the current study was to investigate the occurrence of personalization in the social media content of Members of European Parliament during their routine period of work. It adopted multimodal perspective taking both Facebook and Twitter content into account. The study also drew on three cases with dissimilarities on the country-level, mainly Poland, Germany and Ireland, and explored the individual-level variation, such as gender and age, political affiliation, length of tenure and the engagement in the work of Parliament of the MEPs.
The present research has shown that almost half of the analysed social media posts did not reveal any traces of personalization. Following Kruikemeier (2014a) it could be argued that social media are “personalized per definition” (p. 51). In the case of personalized content, the use of different dimensions varied. Individualization encompassing content on
professional activities appeared most often. The finding corresponds with the results of Hermans and Vergeer (2012), who discovered that on their websites during EP elections 2009 that politicians predominantly disclosed professional information. Emotionalization was not much employed, but a clear dominance of positive emotions could be traced if emotions were evident. A small amount of negative emotions could support the claim that there is not much evidence for a rise in negative campaigning in Europe (Walter, 2013). Furthermore, as in the case of Hermans and Vergeer’s findings (2012), the present research does not confirm previous studies (Hagemann, Jankowski & Voerman, 2005; Van Aelst, 2002), which conclude that personalization within politics will intensify and become increasingly focused on the personal lives of politicians. MEPs rarely disclosed information about their private life, which was reflected in the low levels of privatization. Following Hermans and Vergeer (2012), it could therefore be claimed that politicians “do not provide the audience with information that would otherwise not be public” (p. 81). Individualization dealing with professional qualities was the least utilised among all the dimensions. A possible explanation could be that during periods outside elections, the politicians’ emphasis switches from self-promotion to self-expression and dissemination of information.
The findings also demonstrated slight differences in the use of personalization between three analysed countries. Polish MEPs employed the highest amounts of personalization in their social media communication, German MEPs the lowest, whereas Ireland was situated in between the two. The differences correspond with the Hermans and Vergeer’s research (2012), where personalization strategies used on Polish candidate websites were also higher than in Ireland and Germany. Following Balmas and Sheafer (2013) it might be speculated that levels of political personalization depend on the perceived
proximity towards EU, with more “distant” countries focusing more on personalities than on political aspects. Moreover, differences between countries could be interpreted in terms of political system, geographical region and political trust (Hermans & Vergeer, 2012). A year of accession to the European Union and familiarity with EU politics might also play a role (Lilleker & Koc-Michalska, 2013). The fact that MEPs from Poland used more personalization on their social media, could therefore be associated with country’s low political trust and short European and democratic tradition. On the other hand, use of personalization was lower in the countries which have belonged to the EU for longer, do not share the post-communist legacy and are characterized by higher levels of political trust.
As hypothesized, the characteristics and features of the two analysed social media networks seem to have practical implications on the levels of personalization within MEPs’ content, which was indeed higher on Facebook than on Twitter. This result coincides with the study of Enli and Skogerbø (2013), who found that Norwegian politicians clearly distinguished between Facebook and Twitter and were well aware of the more private, less political and more intimate character of Facebook. Twitter, however, is said to be more about conversation than identity, with less value placed on building relationships (Kietzmann, Hermkens, McCarthy & Silvestre, 2011).
In regard to other hypotheses, differences in the levels of personalization cannot be attributed to the demographic and individual characteristics of MEPs. The study has been unable to demonstrate significant differences on the basis of political affiliation, age, length of incumbency and the levels of participation of the MEPs. Only gender approached significance, which could offer modest support for claims that males and females have different communication styles (Dow & Tonn, 1993; Parry-Giles & Parry-Giles 1996,
Argamon, Koppel, Fine & Shimoni, 2003; Newman, Groom, Handelman & Pennebaker, 2008; Mukherjee, Liu, 2010). The abovemenioned independent variables were also unable to predict variance in the frequency of depersonalization. It can therefore be concluded that other explanatory variables must be sought elsewhere – for example, within interpersonal orientations and psychological traits of the politicians. As stated by Enli and Skogerbø (2013) personality may affect the way politicians use social media, which could also be the case as far as personalization is concerned. In fact, there have been several studies that pointed to links between personality and the use of social media (Amichai-Hamburger & Vinitzky, 2010; Ryan & Xenos, 2011; Moore & McElroy, 2012; Hughes, Rowe, Batey & Lee, 2012; Panek, Nardis & Konrath, 2013; Seidman, 2013). Thus, it would be advisable to conduct a study relating levels of personalization and the personality traits of MEPs by utilizing a survey comprising, for instance, from the Big Five Inventory (BFI), the Social and Emotional Loneliness Scale for Adults (SELSA-S), the Narcissistic Personality Inventory (NPI-29) and the Revised Cheek and Buss Shyness Scale (RCBS). As argued by Vergeer and Hermans (2013), a good starting point might be a more qualitative approach, as such a large-scale research “might be very difficult to organize, requiring a survey among politicians and candidates” (p. 16).
With respect to methodology, as stated by Van Aelst, Sheafer and Stanyer (2011) it is “the lack of conceptual clarity and the absence of a common operationalization that are major causes of the unclear or conflicting conclusions about the personalization of political news” (p. 214). Thus, present research utilised a comprehensive model for the analysis, with three dimensions of personalization – individualization, privatization, and emotionalization, based on previous studies and theories (Van Santen & Wan Zoonen, 2010; Van Aelst,
Sheafer & Stanyer, 2011, Hermans & Vergeer, 2012; Kruikemeier 2014a). It is acknowledged that the measurements of personalization employed in the study were basic. The simplicity and the use of dichotomous categories, however, increased intercoder reliability. Moreover, proposed measurements are replicable and enabled comparison across both social media platforms and different countries.
Analysis of ten posts per MEP offered a glimpse into the politicians’ use of personalization on social media. Yet, the sample size and the selection of countries are still limited, and thus hamper the ability to make broader generalisations from the results. Further studies should assess whether the findings at hand hold across a larger sample of countries. Additionally, a cross-national research with a higher amount of cases could offer some new insight into variation within personalization based on the political cultures of different EU member states. Additionally, as expressed by Larsson (2014), “permanent campaign by definition is something that takes place over time” (p. 163). Therefore, a further longitudinal research looking into the differences in the presence and types of personalization on social media of the Members of the European Parliament is needed. Moreover, to develop further insight into the use of personalization, it could be interesting to compare the social media content of MEPs with the one of national parliamentarians. As anticipated by Hermans and Vergeer (2012), the use of personalization within EU and national context might differ, due to the fact that European elections are regarded as second-order elections (Reif & Schmitt, 1980), with lower public interest, lower media attention and lower stakes.
All in all, the research laid the foundations for further studies. It is recommended that monitoring of political personalization within social media of MEPs continues, both due to the rapidly evolving nature of social media within a political context and the nature of
personalization per se. The assumption is that through personalization, “politicians create a stronger bond with people, going beyond the professional one, that will lead to closing the psychological distance between politician and citizen” (Vergeer, Hermans & Sams, 2011). This is particularly significant for the Members of the European Parliament, who struggle to connect with citizens (Vesnic-Alujevic, 2013).
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Appendix
General instructions for coding
The unit of coding is a single tweet or Facebook post in a form of a written text. The data to analyse is provided in the form of Excel spread sheet. Five last tweets and Facebook posts of each MEP were collected on 15 Mach, 2015 using the data collection program “Facepager“.
Candidate’s info Name and surname
Q1: What is the name and surname of the MEP?
Explanation: copy and paste the name and surname of the politician who created Tweet or Facebook post from dataset in Excel.
Country
Q2: What is the country that MEP is representing?
1 = Ireland 2 = Poland 3 = Germany
Explanation: write code for the country of the MEP based on the dataset in Excel.
Political affiliation
Q3: What is the political affiliation of the MEP?
1 = left and centre-left 2 = centre
3 = right and centre-right 99 = not applicable
Gender
Q4: What is the gender of the MEP?
1 = woman 2 = man
Explanation: write code for the gender of the politician based on the dataset in Excel.
Age
Q5: What is the age of the MEP?
Explanation: copy and paste the age of the politician from the dataset in Excel.
Tenure
Q6: What is the tenure of the MEP?
Explanation: copy and paste the number of years in office from the dataset in Excel.
Participation
Q7: What is the participation in roll-call votes of the MEP (data from Votewatch)?
1 = 0%-5% (< 5) 2 = 5%-10% (< 10) 3 = 10%-15% (< 15) 4 = 15%-20% (< 20) 5 = 20%-25% (< 25) 6 = 25%-30% (< 30) 7 = 30%-35% (< 35) 8 = 35%-40% (< 40) 9 = 40%-45% (< 45) 10 = 45%-50% (< 50)
11 = 50%-55% (< 55) 12 = 55%-60% (< 60) 13 = 60%-65% (< 65) 14 = 65%-70% (< 70) 15 = 70%-75% (< 75) 16 = 75%-80% (<80) 17 = 80%-85% (<85) 18 = 85%-90% (<90) 19 = 90%-95% (<95) 20 = 95%-100%
99 = not applicable (Martin Schulz, European Parliament President)
Explanation: assess the participation of MEP based on the dataset in Excel.
Content
Tweet or Facebook posts are the units of analysis. All questions and codes primarily pertain to what can be detected in the tweet or Facebook post. Read the tweet or Facebook post well before you start coding.
Social media platform
Q8: What is the type of social media being analysed?
1 = Twitter 2 = Facebook
Explanation: Indicate whether you analyse a tweet or Facebook post.
Primary topic of the tweet/ post
Note: You can code only one main topic. 1 = Agriculture
Explanation: the tweet/ post is about an agricultural topic, e.g. cultivation of animals, plants, farming law, agriculture subsidies.
E.g. All the more reason to oppose GMO
http://www.theecologist.org/News/news_analysis/2805343/carving_up_africa_aid_donors_a nd_agribusiness_plot_the_great_seed_privatization.html”
2 = Culture
Explanation: the tweet/ post is about culture, e.g. books, music cultural events such as concert, play, museum, ballet, festival.
E.g. And the Oscar for best foreign-language film goes to… Ida! “Share” to help spread the
good news! And read more about the film, which also received the Parliament’s LUX Prize
3 = Crime
Explanation: the tweet/ post deals with crime e.g. murder, robbery, bomb attack etc.
E.g. @irishexaminer: 2 charged after cannabis find Offaly | http://exa.mn/olt (RMC) " that's
the war won then #not
4 = Defense/military/ war
Explanation: the tweet/ post refers to defense or war, e.g. armament, weapons, military action, military cooperation, military conflict.
E.g. Head of the European Commission, Jean Claude Juncker, this week caused a stir with
his call for an EU Army. Good article in today's Irish Times analysing the political background to this statement http://www.irishtimes.com/news/world/europe/jean-claude-juncker-call-for-a-european-army-has-much-to-do-with-optics-1.2135787
5 = Economy/finance/ business/ trade
Explanation: the tweet/ post deals with economic, financial, business or trade topic, e.g. budgeting, taxes, financial crisis, Euro, Transatlantic Trade and Investment Partnership (TTIP) or economic development such as creating jobs.
E.g. The Guardian reports: 'German 'hypocrisy' over Greek military spending has critics up
in arms - Athens' fondness for weaponry, and willingness of Germany and France to feed it, under fire as Greece struggles with debt crisis
6 = Education
Explanation: the tweet/ post is about educational matters, e.g. university curriculum, subsidies for education, new study programs, exchange programs, students etc. E.g. Great to meet students from UL this morning,I enjoyed it,hope you did. 7 = Environment/sustainability
Explanation: the tweet/ post deals with environmental issues e.g. climate change, energy, water, new sustainability programs, natural disaster.
E.g. Brilliant to see such a good turnout for the national spring clean in Dominics organised
by Tallaght Community Council.
8 = Health
Explanation: the tweet/ post deals with health issues, e.g. health system, health insurance, epidemics, immunisation programs.
E.g. The opinion published this morning is a damning indictment of this Government and
shows clearly the impact the recruitment moratorium in the public sector has had on our health services. It also shows the complete disregard that our Government has for the working conditions of our front line health staff. It shows the clear need for an adequately
funded and properly resourced health system, which addresses the health needs of our population: http://www.sinnfein.ie/contents/34202
9 = Immigration/asylum policy
Explanation: the tweet/ post is about immigration or asylum policy, e.g. refugees, illegal trafficking.
E.g. Photo of installation in plaza in front of European Parliament in Brussels yesterday,
symbolising Sunday's tragedy in the Mediterranean. As many as 1,800 migrants will have died so far trying to cross the Mediterranean since the start of this year. Estimates say around 21,000 have made the voyage successfully. People fleeing from war, devastation and terror from countries in Africa and the Middle East.
10= Institutional
Explanation: the tweet/ post deals with inner working in institutions and their competences, working groups, job opening, applications etc.
E.g. We need to strengthen the MEPs Code of Conduct - and I was very pleased to host the
AlterEU event in Brussels yesterday, where we also launched this new guide for MEPs
11 = International relations/ foreign policy
Explanation: the tweet/ post refers to international relations between countries, foreign policy, e.g. diplomatic missions, international treaties, diplomacy, international summits. E.g. Great BBC piece explaining ISDS http://bbc.in/1y3dsrn 'Countries didn't understand
potential impact of investment/ISDS photo-op treaties'
12 = Law/ legislature
Explanation: the tweet/ post deals with judicial issues, including courts, trials, court decisions or legislature such as laws, bills
