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.
- P. Ekman. 1992. “An argument for basic emotions,” Cognition & emotion, vol. 6, no. 3–4, pp. 169–200. DOI: https://doi.org/10.1080/02699939208411068Google ScholarCross Ref
- D. A. Sauter, F. Eisner, P. Ekman, and S. K. Scott. 2010. “Cross-cultural recognition of basic emotions through nonverbal emotional vocalizations,” Proceedings of the National Academy of Sciences, vol. 107, no. 6, pp. 2408–2412. https://doi.org/10.1073/pnas.0908239106Google ScholarCross Ref
- R. Plutchik. 1980. “A general psychoevolutionary theory of emotion,” in Theories of emotion, Elsevier, pp. 3–33.Google Scholar
- S. M. Mohammad and P. D. Turney. 2013. “Crowdsourcing a word–emotion association lexicon,” Computational intelligence, vol. 29, no. 3, pp. 436–465.Google ScholarCross Ref
- C. Hutto and E. Gilbert. 2014. “Vader: A parsimonious rule-based model for sentiment analysis of social media text,” in Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, no. 1.Google Scholar
- S. Aral and D. Eckles. 2019. “Protecting elections from social media manipulation,” Science, vol. 365, no. 6456, pp. 858–861.Google ScholarCross Ref
- L. M. Kruse, D. R. Norris, and J. R. Flinchum. 2018. “Social media as a public sphere? Politics on social media,” The Sociological Quarterly, vol. 59, no. 1, pp. 62–84.Google ScholarCross Ref
- Mandal, K. Ghosh, S. Ghosh, and S. Mandal. 2021. “Unsupervised approaches for measuring textual similarity between legal court case reports,” Artificial Intelligence and Law, pp. 1–35.Google Scholar
- K. W. Boyack 2011. “Clustering more than two million biomedical publications: Comparing the accuracies of nine text-based similarity approaches,” PloS one, vol. 6, no. 3, p. e18029.Google ScholarCross Ref
- D. J. MacKay. 1992. “Bayesian interpolation,” Neural computation, vol. 4, no. 3, pp. 415–447.Google ScholarDigital Library
- M. E. Tipping. 2001. “Sparse Bayesian learning and the relevance vector machine,” Journal of machine learning research, vol. 1, no. Jun, pp. 211–244.Google ScholarDigital Library
- D. P. Kingma and J. Ba. 2014. “Adam: A method for stochastic optimization,” arXiv preprint arXiv:1412.6980.Google Scholar
- C. J. Vargo, L. Guo, M. McCombs, and D. L. Shaw. 2014. “Network issue agendas on Twitter during the 2012 US presidential election,” Journal of Communication, vol. 64, no. 2, pp. 296–316.Google ScholarCross Ref
- B. Joyce and J. Deng. 2017. “Sentiment analysis of tweets for the 2016 US presidential election,” in 2017 ieee mit undergraduate research technology conference (urtc). pp. 1–4.Google Scholar
- D. A. Pereira. 2021. “A survey of sentiment analysis in the Portuguese language,” Artificial Intelligence Review, vol. 54, no. 2, pp. 1087–1115.Google ScholarDigital Library
- S. Aral. 2020. The Hype Machine: How Social Media Disrupts Our Elections, Our Economy, and Our Health–and How We Must Adapt. Currency.Google Scholar
- M. D. Conover, B. Gonçalves, J. Ratkiewicz, A. Flammini, and F. Menczer. 2011.“Predicting the political alignment of twitter users,” in 2011 IEEE third international conference on privacy, security, risk and trust and 2011 IEEE third international conference on social computing. pp. 192–199.Google Scholar
- D. Hagar. 2015. “# vote4me: The impact of Twitter on municipal campaign success,” in Proceedings of the 2015 International Conference on Social Media & Society. pp. 1–7.Google ScholarDigital Library
- Q. Zhang, Y. Gong, J. Wu, H. Huang, and X. Huang. 2016. “Retweet prediction with attention-based deep neural network,” in Proceedings of the 25th ACM international on conference on information and knowledge management. pp. 75–84.Google Scholar
- H.-K. Peng, J. Zhu, D. Piao, R. Yan, and Y. Zhang. 2011. “Retweet modeling using conditional random fields,” in 2011 IEEE 11th International Conference on Data Mining Workshops pp. 336–343.Google Scholar
- J. Chen, M. S. Hossain, and H. Zhang. 2020. “Analyzing the sentiment correlation between regular tweets and retweets,” Social Network Analysis and Mining, vol. 10, no. 1, pp. 1–9.Google ScholarCross Ref
- M. Aparicio and C. J. Costa. 2012. “Collaborative systems: characteristics and features,” in Proceedings of the 30th ACM international conference on Design of communication. pp. 141–146. DOI: https://doi.org/doi.org/10.1145/2379057.2379087Google ScholarDigital Library
- S. Aparicio, J. T. Aparicio, and C. J. Costa. 2019. “Data Science and AI: trends analysis,” in 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). pp. 1–6. DOI: https://doi.org/10.23919/CISTI.2019.8760820Google Scholar
- C. J. Costa and J. T. Aparicio. 2020. “POST-DS: A Methodology to Boost Data Science,” in 2020 15th Iberian Conference on Information Systems and Technologies (CISTI) pp. 1–6. DOI: https://doi.org/10.23919/CISTI49556.2020.9140932Google Scholar
- C. J. Costa and M. Aparicio. 2013. “Social networks: intentions and usage,” in Proceedings of the 2013 International Conference on Information Systems and Design of Communication. pp. 101–107. DOI: https://doi.org/10.1145/2503859.2503875Google ScholarDigital Library
- C. J. Costa, M. Aparício, and A. S. Braga. 2012. ‘Design of communication: a review of theories and models’, New York, NY, USA, 2012, pp. 15–19. doi: 10.1145/2311917.2311921.Google ScholarDigital Library
- J. T. Aparicio, J. Salema de Sequeira and C. J. Costa. 2021. "Emotion analysis of Portuguese Political Parties Communication over the covid-19 Pandemic," 2021 16th Iberian Conference on Information Systems and Technologies (CISTI), 2021, pp. 1-6, DOI: https://doi.org/10.23919/CISTI52073.2021.9476557Google Scholar
- M. Aparicio, & C. Costa. 2001. A First step Toward E-politics: A Better Informed Citizen, in S. Bjornestad, R. Moe, A. Morch, A. Opdahl (Eds.), Proceedings of IRIS24: The 24th Information Systems Research Seminar in Scandinavia Vol. 1; 2001, pp.23-34, ISBN 82-7354072-3.Google Scholar
Recommendations
The megaphone of the people? Spanish SentiStrength for real-time analysis of political tweets
Twitter is an important platform for sharing opinions about politicians, parties and political decisions. These opinions can be exploited as a source of information to monitor the impact of politics on society. This article analyses the sentiment of 2,...
A sentiment analysis of audiences on twitter: who is the positive or negative audience of popular twitterers?
ICHIT'11: Proceedings of the 5th international conference on Convergence and hybrid information technologyMicroblogging is a new informal communication medium of blogging that differs from a traditional blog in which content is much shorter. Microbloggers post about topics that describe their current status. Twitter is a popular microblogging service and ...
Political Communication and Influence through Microblogging--An Empirical Analysis of Sentiment in Twitter Messages and Retweet Behavior
HICSS '12: Proceedings of the 2012 45th Hawaii International Conference on System SciencesMicroblogging services such as Twitter are said to have the potential for increasing political participation. Given the feature of 'retweeting' as a simple yet powerful mechanism for information diffusion, Twitter is an ideal platform for users to ...
Comments