# Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment

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6 Table 4: Share of tweets and election results 1.65% In conclusion, the mere number of tweets mentioning a political party can be considered a plausible reflection of the vote share and its predictive power even comes close to traditional election polls. Table 5: Forecast accuracy of various election polls After extracting the absolute strength of each party from the message volume, we now turn to the relationships between parties. This is all the more relevant, as all parties were far from an absolute majority in the weeks preceding the federal election and a coalition government was on the horizon. As many tweets mention more than one political party, we investigate whether joint mentions reflect prevailing or even upcoming political ties. To make the comparison easier, we focus on tweets mentioning only two parties. Based on the overall probability that any one party is mentioned in these tweets, a conditional probability that two parties are mentioned together can be computed. If all combinations were equally likely, this conditional probability should equal the observed share of tweets mentioning these two parties. Due to different base rates, we divide the observed share of joint mentions by the conditional probability to derive a comparative measure. If share(cdu, CSU) represents the share of observed joint mentions of these two parties, the relative frequency (f), is calculated as follows: (2) f = share( CDU, CSU ) [ P( CDU CSU ) + P( CSU CDU )]/ 2 The relative frequency illustrates how often two parties are mentioned together relative to the random probability based on the overall "share of voice" of the individual parties. If f equals 1.5 the share of observed joint mentions is 50% higher than pure chance would suggest. Table 6 shows the relative frequency for all combinations of two parties based on all tweets mentioning more than on party (n = ). Not surprisingly, the combined mentioning of sister parties CDU and CSU was the most frequent (f = 1.25), whereas CSU and the left-ofcenter parties (SPD, Green party, and Linke) were mentioned together the least. While the governing coalition of CDU and SPD are naturally mentioned jointly quite frequently, the Union parties (CDU and CSU) are associated most closely with its desired coalition partner at that time, the FDP. The parties of the left side of the political spectrum are associated with each other more often than with the rightof-center parties (CDU, CSU, and FDP). In sum, the joint mentions of political parties accurately reflect the political ties between the parties. We conclude that despite the fact that the Twittersphere is no representative sample of the German electorate, the activity prior to the election seems to validly reflect the election outcome. Table 6: Relative frequency of joint mentions Conclusion and further research We analyzed over 100,000 Twitter messages mentioning parties or politicians prior to the German federal election Overall, we found that Twitter is indeed used as a platform for political deliberation. The mere number of tweets reflects voter preferences and comes close to traditional election polls, while the sentiment of Twitter messages closely corresponds to political programs, candidate profiles, and evidence from the media coverage of the campaign trail. With respect to our first research question, we found more than one third of all messages to be part of a conversation indicating that Twitter is not just used to spread political opinions, but also to discuss these opinions with other users. While we find evidence of a lively political debate on Twitter, this discussion is still dominated by a small number of users: only 4% of all users accounted for more than 40% of the messages. With respect to our second research question, we found the sentiment profiles of politicians and parties to plausibly reflect many nuances of the election campaign. For example, the similar profiles of Angela Merkel und Frank- Walter Steinmeier, mirror the consensus-oriented political 183

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