Abstract
India is one of the largest democracies in the world where the Lok Sabha and the Rajya Sabha elections are held every five years. Nowadays, social media acts as an important and inexpensive platform for propagating messages of the political parties. In the present study, a methodology is proposed by combining sentiment analysis and graph techniques to look into the trending hashtag networks propagated by the political parties using Twitter. The demonstration of the proposed methodology is done on the trending hashtag’s information collected from Twitter on the Uttar Pradesh (U.P) state elections, 2022.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Twitter. Retrieved 15 Mar 2022, from https://twitter.com/home
Neogi, A.S., Garg, K.A., Mishra, R.K., Dwivedi, Y.K.: Sentiment analysis and classification of Indian farmers’ protest using twitter data. Int. J. Inf. Manag. Data Insights 1(2), 100019 (2021)
Chintalapudi, N., Battineni, G., Di Canio, M., Sagaro, G.G., Amenta, F.: Text mining with sentiment analysis on seafarers’ medical documents. Int. J. Inf. Manag. Data Insights 1(1), 100005 (2021)
Twitter: Second quarter 2016 report (2016)
Twitter: Twitter IPO prospectus (2013)
DuVander, A.: Which APIs are handling billions of requests per day? Programmable Web (2012)
Alexa.com: Website traffic ranking (2017)
Satish, M., Srinivasa Rao, P., RamakrishnaMurty, M.: Identification of natural disaster affected area using Twitter. In: AISC Springer ICETC-2019, vol. 3, pp. 792–801 (2019)
Khan, A., Zhang, H., Shang, J., Boudjellal, N., Ahmad, A., Ali, A., Dai, L.: Predicting politician’s supporters’ network on Twitter using social network analysis and semantic analysis. Sci. Program. 2020 (2020)
Melo, C., Lechevallier, Y., Aufare, M.A.: Social Networks Analysis: A Case Study on the Twitter Network
Himelboim, I., Smith, M., Shneiderman, B.: Tweeting apart: applying network analysis to detect selective exposure clusters in Twitter. Commun. Methods Measures 7(3–4), 195–223 (2013)
Hansen, D.L., Shneiderman, B., Smith, M.A.: Analyzing social media networks with NodeXL: insights from a connected world (2010). ISBN 978-0-12-382229-1
Oud, A., Sarah, T.A., Alohaideb, W.: Hybrid sentiment analyser for Arabic tweets using R. In: 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K), vol. 1, pp. 417–424 (2015)
Fiaidhi J et al (2012) Opinion mining over Twitter space: classifying tweets programmatically using the R approach. In: Seventh International Conference on Digital Information Management (ICDIM), pp. 313–319. IEEE
Ansari, M.Z., Aziz, M.B., Siddiqui, M.O., Mehra, H., Singh, K.P.: Analysis of political sentiment orientations on Twitter. Procedia Comput. Sci. 167, 1821–1828 (2020)
Smith, M.A., Shneiderman, B., Milic-Frayling, N., Mendes Rodrigues, E., Barash, V., Dunne, C., Capone, T., Perer, A., Gleave, E.: Analyzing (social media) networks with nodexl. In: Proceedings of the Fourth International Conference on Communities and Technologies, pp. 255–264 (2009)
Bastian, M., Heymann, S., Jacomy, M.: Gephi: an open source software for exploring and manipulating networks. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 3, no. 1, pp. 361–362 (2009)
Waila, P., Singh, V.K., Singh, M.K.: Evaluating machine learning and unsupervised semantic orientation approaches for sentiment analysis of textual reviews. In: 2012 IEEE International Conference on Computational Intelligence and Computing Research, pp. 1–6. IEEE (2012)
Asghar, M.Z., Khan, A., Ahmad, S., Kundi, F.M.: A review of feature extraction in sentiment analysis. J. Basic Appl. Sci. Res. 4(3), 181–186 (2014)
Hutto, C.J., Gilbert, E.E.: VADER: a parsimonious rule-based model for sentiment analysis of social media text. In: Eighth International Conference on Weblogs and Social Media (ICWSM-14), Ann Arbor, MI (2014)
Kumar, P., Sinha, A.: Information diffusion modeling and analysis for socially interacting networks. Soc. Netw. Anal. Min. 11(1), 1–18 (2021)
ABP News: CVoter survey January UP assembly election 2022 opinion polls vote share seat sharing KBM BJP SP BSP Congress (2022 Jan 29). Retrieved 17 Apr 2022 from https://tinyurl.com/2p8swu64
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Patra, C., Pushparaj Shetty, D., Chakraborty, S. (2023). An Approach for Predicting Election Results with Trending Twitter Hashtag Information Using Graph Techniques and Sentiment Analysis. In: Bhateja, V., Yang, XS., Lin, J.CW., Das, R. (eds) Evolution in Computational Intelligence. FICTA 2022. Smart Innovation, Systems and Technologies, vol 326. Springer, Singapore. https://doi.org/10.1007/978-981-19-7513-4_29
Download citation
DOI: https://doi.org/10.1007/978-981-19-7513-4_29
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-7512-7
Online ISBN: 978-981-19-7513-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)