Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Ramesh, Ashwini
- Algorithmic Analysis of Political Tweets : A Systematic Literature Review
Abstract Views :236 |
PDF Views:5
Authors
Affiliations
1 Department of Mass Communication and Journalism, Bengaluru City University, Bengaluru – 560001, Karnataka, IN
1 Department of Mass Communication and Journalism, Bengaluru City University, Bengaluru – 560001, Karnataka, IN
Source
Journal of Information and Knowledge (Formerly SRELS Journal of Information Management), Vol 59, No 4 (2022), Pagination: 185-195Abstract
This study investigates the trends and challenges in information science with a special focus on political tweets. The past decade has witnessed a transformation in information mining, extraction and production using algorithms on social media platforms. The unique data structure of Twitter has gained scholarly attention for its intelligence to produce voluminous information which is convenient and rapid. But the efficiency of Twitter as a platform to obtain political knowledge remains a question. Various socio-technological research methods have emerged making Twitter an integrated topic of study for scholars from media studies, computer science and information science. The big data environment provides hashtags, @-mentions, and various digital affordances necessitating its study to be an integral part of social science research. Thus, the systematic literature review aims to examine tweeting patterns of political leaders to study variables such as ideology diffusion, polarization, political issues, digital campaigns etc. The study also examines computational research methods to retrieve Twitter data pertaining to political information. Academic investigation consists of approaches to automated data collection on Twitter, pre-processing techniques using R and Python, machine learning procedures and sentiment analysis used on Twitter data. The study showcases India’s stand in adopting the niche socio-technological methods in social science research.Keywords
Algorithmic Analysis, Information Science, Political Communication, Twitter.
References
- Ahmed, S., Cho, J. and Jaidka, K. (2017). Leveling the playing field: The use of Twitter by politicians during the 2014 Indian general election. Telematic and Informatics, 34, 1377-1386. https://dx.doi.org/10.1016/j.tele.2017.09.005.
- Anmol, P., Ramaravind, K.M., Monojit, C. and Joyojeet, P. (2020). Topical focus of political campaigns and its impact: Findings from politicians’ Hashtag use during the 2019 Indian elections. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW1), 1-14. https://doi.org/10.1145/3392860.
- Beltran, J., Gallego, A., Huidobro, A., Romero, E. and Padro, L. (2020). Male and female politicians on Twitter: A machine learning approach. European Journal of Political Research, 60(1), 239-251. https://doi.org/10.1111/1475-6765.12392.
- Bennett, W.L., and Segerberg, A. (2012). The Logic of connective action: Digital mesia and the personalization of contentious politics. Information, Communication and Society, 15(5), 739-768. https://doi.org/10.1080/1369118X.2012.670661.
- Bozarth, L., Panda, A., Budak, C. and Pal, J. (2020). From greetings to corruption: Politicians, political parties, and tweeting in India. Proceedings of the 2020 International Conference on Information and Communication Technologies and Development, 8, 1-13. https://doi.org/10.1145/3392561.3394636.
- Bruns, A., and Highfield, T. (2015). Is Habermas on Twitter? The Routledge Companion to Social Media and Politics. Routledge, https://doi.org/10.4324/9781315716299.
- Bruns, A. and Highfield, T. (2013). Political networks on Twitter: Tweeting the Queensland State election. Information, Communication and Society, 16(5), 667-691. https://doi.org/10.1080/1369118X.2013.782328.
- Chadha, K. and Guha, P. (2016). The Bharatiya Janata Party’s online campaign and citizen involvement in India’s 2014 election. International Journal of Communication, 10, 4389-4406.
- D’heer, E. and Verdegem, P. (2014). Conversations about the elections on Twitter: Towards a structural understanding of Twitter’s relation with the political and the media field. European Journal of Communication, 29(6), 720-734. https://doi.org/10.1177/0267323114544866.
- Du, A. and Gregary, S. (2016). The Echo Chamber Effect in Twitter: Does Community Polarization Increase? In: Cherifi, H., Gaito, S., Quattrociocchi, W., Sala, A. (eds) Complex Networks and their Applications V. Complex Networks, Studies in Computational Intelligence; Springer. https://doi.org/10.1007/978-3-319-50901-3_30.
- Evans, H. K. and Clark, J. H. (2015). You tweet like a girl: How female candidate’s campaign on Twitter. American Politics Research, 44(2), 326-353. https://doi.org/10.1177/1532673X15597747.
- Fink, A. (2014). Conducting research literature reviews: From the Internet to paper (4th ed.). Thousand Oaks, CA: Sage.
- Gayo-Avello, D. (2013). A meta-analysis of state-of-the-art electoral prediction from Twitter data. Social Science Computer Review, 31(6), 649-679. https://doi.org/10.1177/0894439313493979.
- Gonawela, A., Kumar, R., Thawani, U., Ahmad, D., Chandrasekaran, R. and Pal, J. (2020). The Anointed Son, the Hired Gun, and the Chai Wala: Enemies and Insults in Politicians Tweets in the Run-Up to the 2019 Indian General Elections. Proceedings of the 53rd Hawaii International Conference on Systems Sciences; p. 2878-2887. https://dx.doi.org/10.24251/HICSS.2020.352.
- Goyal, M. (2014, April 6). How BJP, AAP, Congress and their candidates are using social media to woo voters. The Economic Times. http://articles. economictimes. indiatimes.com/2014-04-06/news/48908610_1_social-media-it-cell-fekuexpress
- Gruzd, A. and Roy, J. (2014). Investigating Political Polarization on Twitter: A canadian perspective. Policy and Internet, 6(1), 28-45. https://doi.org/10.1002/1944-2866.POI354.
- Gupta, R., Kumar, J., Agarwal, H. and Kunal. (2020). A Statistical Approach for Sarcasm Detection using Twitter Data. Proceedings of the 4th International Conference on Intelligent Computing and Control Systems (ICICCS); p. 633-638. https://doi.org/10.1109/ICICCS48265.2020.9120917. PMCid:PMC7418887.
- Hardeniya, T. and Borikar, D. A. (2016). Dictionary based approach to sentiment analysis - A review. International Journal of Advanced Engineering, Management and Science, 2(5), 317-322.
- Hemsley, J., Stromer-Galley, J., Semaan, B. and Tanupabrungsun, S. (2018). Tweeting to the Target: Candidates’ use of strategic messages and @Mentiona on Twitter. Journal of Information Technology and Politics, 15(1), 3-18. https://doi.org/10.1080/19331681.2017.1338634.
- Howard, P.N., Woolley, and Calo, R. (2018). Algorithms, bots, and political communication in the US 2016 election: The challenge of automated political communication for election law and administration, Journal of Information Technology and Politics, 15(2), 81-93. https://doi.org/10.1080/19331681.2018.1448735.
- Hu, M. and Liu, B. (2004). Mining and Summarizing Customer Reviews. Proceedings of the ACM SIGKDD International Conference on Knowledge, Discovery and Data Mining (KDD); p. 22-25. https://doi.org/10.1145/1014052.1014073.
- Jaffrelot, C. (2010). Religion, caste, and Politics in India. Primus Books, Delhi. https://doi.org/10.1093/obo/9780195399318-0095.
- Jaffrelot, C. (2015). The Modi-centric BJP 2014 election campaign: New techniques and old tactic. Contemporary South Asia, 23(2), 151-166. https://doi.org/10.1080/09584935.2015.1027662.
- Jaidka, K. and Ahmed, S. (2015). The 2014 Indian General Election on Twitter: An analysis of Changing Political Traditions. Proceedings of the Seventh International Conference on Information and Communication Technologies and Development; 43, p. 1-5. https://doi.org/10.1145/2737856.2737889.
- Jamilu, A., Azuraliza, A.B. and Mohd, R.Y. (2018). Hybrid N-gram model using Naïve Bayes for classification of political sentiments on Twitter. Neutral Computing and Applications, 31, 9207-9220. https://doi.org/10.1007/s00521-019-04248-z.
- Jungherr, A. (2016). Twitter use in election campaigns: A systematic literature review. Journal of Information Technology and Politics, 13(1), 72-91. https://doi.org/10.1080/19331681.2015.1132401.
- Kruikemeier, S. (2014). How political candidates use Twitter and the impact on voters. Computers in Human Behavior, 34, 131-139. https://doi.org/10.1016/i.chb.2014.01.025.
- Lorentzen, D. G. (2013). Polarisation in political Twitter conversations. Aslib Journal of Information Management, 66(3), 329-341. https:/doi.org/10.1108/ajim-09-2013-0086.
- Marco, C. and Enrico, G. C. (2018). Revealing Political Sentiment with Twitter: The Case Study of the 2016 Italian Constitutional Referendum. Proceedings of IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 861-868. https://doi.org/10.1109/ASONAM.2018.8508243.
- Molyneux, L. and Mourao, R., R. (2017). Political journalists’ normalization of Twitter: Interaction and new affordances. Journalism Studies, 20(2), 248-266. https://doi.org/10.1080/1461670X.2017.1370978.
- Nooralahzadeh, F., Arunachalam, A. and Chiru, C. (2013). 2012 Presidential Elections on Twitter - An Analysis of how the US and French Election were Reflected in Tweets. In: I. Dumitrache, A.M. Florea, & F. Pop (Eds.), CSCS’13: Proceedings of the 2013 19th International Conference on Control Systems and Computer Science, Washington, DC: IEEE Computer Society; p. 240-246. https://doi.org/10.1109/CSCS.2013.72.
- Ozlem, I., Mehmet, S., Nilay, Y. and Naci, K. (2014). Political use of Twitter: The Case of Metropolitan Mayor Candidates in 2014 Local Elections in Turkey. Proceedings of the 8th International Conference on Theory and Practice of Electronic Governance; p. 41-50. https://doi.org/10.1145/2691195.2691219.
- Pandarachalil, R., Sendilkumar, S. and Mahalakshmi, G. S. (2014) Twitter sentiment analysis for large-scale data: An unsupervised approach. Cogn. Comput., 7, 254-262. https://doi.org/10.1007/s12559-014-9310-z.
- Perl, J., Wagner, C., Kunegis, J. and Staab, S. (2015). Twitter as a Political Network: Predicting the following and unfollowing behaviour of German Politicians. Proceedings of the ACM Web Science Conference; p. 51:1-2. https://doi.org/10.1145/2786451.2786506. PMCid:PMC4742053
- Plummer, M., Palomino, M. A. and Masala, G. L. (2017). Analysing the Sentiment Expressed by Political Audiences on Twitter: The case of the 2017 2017 UK General Election. Conference Proceedings of the 2017 International Conference on Computational Intelligence (CSCI); p. 1449-1454. https://doi.org/10.1109/CSCI.2017.253.
- Posegga, O. and Jungherr, A. (2019). Characterizing Political Talk on Twitter: A Comparison between Public Agenda, Media Agendas, and the Twitter Agenda with Regard to Topics and Dynamics. Proceedings of the 52nd Hawaii Conference on System Sciences; p. 2590-2599. https://hdl.handle.net/10125/59697.
- Rajadesingan, A., Panda, A. and Pal, J. (2020). Leader or Party? Personalization in Twitter Political campaigns during the 2019 Indian elections. Proceedings of International Conference on Social Media and Society, p. 174-183. https://doi.org/10.1145/3400806.3400827.
- Rill, S., Reinel, D., Scheidt, J. and Zicari, R., V. (2014). PoliTwi: Early detection of emerging political topics on twitter and the impact on concept-level sentiment analysis. Knowledge-Based Systems, 69, 24-33. https://doi.org/10.1016/i.knosys.2014.05.008.
- Sanger, W. and Thierry, W. (2017). The 2015 Canadian Election in Twitter: A Tidy Algorithmic Analysis. Proceedings of the 2017 International Conference on Computational Science and Computational Intelligence (CSCI); p. 910-915. https://doi.org/10.1109/CSCI.2017.158.
- Seethaler, J. and Melischek, G. (2019). Twitter as a tool for agenda building in election campaigns? The case of Austria. Journalism, 20(8), 1087-1107. https://doi.org/10.1177/1464884919845460.
- Sergio, A. G., Fatima, V. and Joan, F. F. G. (2022). Analysis of the Twitter discourse in the 219 electoral debates in Spain: a comparative algorithmic study. Communication and Society, 35(1), 45-61. https://doi.org/10.15581/003.35.1.45-61.
- Sharma, A. and Ghose, U. (2020). Sentiment analysis of Twitter data with respect to general elections in India. Procedia Computer Science, 173, 325-334. https://doi.org/10.1016/j.procs.2020.06.038.
- Sharma, S. and Shetty, N. P. (2018). Determining the popularity of political parties using Twitter sentiment analysis. Information and Decision Sciences, 701, 21-29. https://doi.org/10.1007/978-981-10-7563-6_3.
- Stiene, P., Peter, V. A., Walter, D., Tim, K., Jeroen, P., Stefaan, W. and David, M. (2021). Comparing automated content analysis methods to distingish issue communication by political parties on Twitter. Computational Communication Research, 3(2), 1-27. https://doi.org/10.5117/CCR2021.2.004.PRAE.
- Sujithra, M. (2018). Sentiment analysis on Twitter Data using Machine Learning Algorithms in Python. Proceedings of the International Conference on Advances in Computing Applications (ICACA-18), NIT Uttarakhand; p. 1-8.
- Tago, K, and Jin, Q. (2018). Influence analysis of emotional behaviours and user relationships based on Twitter data. Tsinghua Science and Technology, 23(1), 104-113. https://doi.org/10.26599/TST.2018.9010012.
- Vaghela, P., Mothilal, R., and Pal, J. (2020). Birds of a caste -How caste hierarchies manifest in retweet behaviour of Indian Politicians. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW 3), 1-24. https://doi.org/10.1145/3432911.
- Vergeer, M., Hermans, L. and Sams, S. (2013). Online social networks and micro-blogging in political campaigning: The exploration of a new campaign tool and a new campaign style. Party Politics, 19(3), 477-501. https://doi.org/10.1177/1354068811407580.
- Yang, X., Chen, B., Maity, M. and Ferrara, E. (2016). Social Politics: Agenda Setting and Political Communication on Social Media. Conference Proceedings on International Conference and Social Informatics; p. 330-334. https://doi.org/10.1007/978-3-319-47880-7_20.
- Yohassen, P., Tampubolon, A. R., Sianturi, L. D., Rifka, D. M. and David, F. P. (2018). Implementation of sentiment analysis on Twitter using Naive Bayes algorithm to know the people responses to debate of DKI Jakarta Governor election. Journal of Physics, 1175, 1-7. https://doi.org/10.1088/1742-6596/1175/1/012102.