This study investigates whether Twitter can serve as a valid indicator of political sentiment and election outcomes. Using LIWC text analysis software, the researchers analyzed over 100,000 tweets from the weeks leading up to the 2009 German federal election. The results show that Twitter is indeed used extensively for political deliberation, with the number of tweets mentioning a political party reflecting the election outcome. Joint mentions of two parties align with real-world political ties and coalitions. The sentiment of tweets closely corresponds to the political positions of parties and politicians, indicating that Twitter content plausibly reflects the offline political landscape. The study also finds that the activity on Twitter can be used to predict the popularity of parties or coalitions in the real world. The number of tweets mentioning a party correlates closely with the election results, with a mean absolute error of 1.65%, which is comparable to traditional election polls. The analysis of joint mentions of political parties shows that these mentions reflect real-world political ties and coalitions. The study concludes that despite the Twittersphere not being a representative sample of the German electorate, the activity prior to the election seems to validly reflect the election outcome. The findings suggest that Twitter can be considered a valid indicator of political opinion. However, the study acknowledges several limitations, including potential biases in the sample and the need for more comprehensive analysis of the context of tweets. Future research should explore more detailed classifications of content and investigate the context of statements more comprehensively.This study investigates whether Twitter can serve as a valid indicator of political sentiment and election outcomes. Using LIWC text analysis software, the researchers analyzed over 100,000 tweets from the weeks leading up to the 2009 German federal election. The results show that Twitter is indeed used extensively for political deliberation, with the number of tweets mentioning a political party reflecting the election outcome. Joint mentions of two parties align with real-world political ties and coalitions. The sentiment of tweets closely corresponds to the political positions of parties and politicians, indicating that Twitter content plausibly reflects the offline political landscape. The study also finds that the activity on Twitter can be used to predict the popularity of parties or coalitions in the real world. The number of tweets mentioning a party correlates closely with the election results, with a mean absolute error of 1.65%, which is comparable to traditional election polls. The analysis of joint mentions of political parties shows that these mentions reflect real-world political ties and coalitions. The study concludes that despite the Twittersphere not being a representative sample of the German electorate, the activity prior to the election seems to validly reflect the election outcome. The findings suggest that Twitter can be considered a valid indicator of political opinion. However, the study acknowledges several limitations, including potential biases in the sample and the need for more comprehensive analysis of the context of tweets. Future research should explore more detailed classifications of content and investigate the context of statements more comprehensively.