Abstract
Political communication in social media has gained increasing importance in the last years. In this study, we analyze the political parties’ communication on Twitter and understand the sentiment of their communication. First by identifying their communication performance regarding the daily number of tweets, favorite tweets, number of retweets per day and per political party. We present a sentiment analysis by the political party using tweets data. In this study, we propose an explanatory model with the main drivers of retweets. To conduct this study, our approach used data analysis and machine learning techniques methods. Results indicate the main determinants that influence future retweets of political posts globally. Here we present a comparison of the communication content between tweets posts and the political parties’ programs available on their institutional websites. We identify the similarities between tweets and formal programs per party and among all parties. This study contributes to analyze the coherence and effectiveness of the political parties’ communication.
Original language | English |
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Title of host publication | Proceedings of the 39th ACM International Conference on the Design of Communication (SIGDOC '21) |
Publisher | ACM - Association for Computing Machinery |
Pages | 63-69 |
Number of pages | 7 |
ISBN (Print) | 978-1-4503-8628-9 |
DOIs | |
Publication status | Published - 12 Oct 2021 |
Event | 39th ACM International Conference on the Design of Communication: Building Coalitions. Worldwide, SIGDOC 2021 - Virtual, Online, United States Duration: 12 Oct 2021 → 14 Oct 2021 Conference number: 39 |
Conference
Conference | 39th ACM International Conference on the Design of Communication: Building Coalitions. Worldwide, SIGDOC 2021 |
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Abbreviated title | SIGDOC 2021 |
Country/Territory | United States |
Period | 12/10/21 → 14/10/21 |
Keywords
- document similarity
- machine learning
- political parties
- sentiment analysis