Tweet Mining from General Elections of a Country

Muhammad Noman Hayat, Nigar Fida, Haroon Khan, Mohammad Sohail


In previous election of a country for its democratic elections in which social media was targeted as a way to convince the social media users to attract their votes, an analysis of BigData on these elections tweets is performed to gather some interesting information. The parties which have been active on social media during elections were identified through hashtag and keyword frequency of occurrences; the top twitter users who influenced the public in election’s were identified by identifying the most re tweeted tweets and finally a comprehensive sentiment analysis were done on the big data set to check “Election trolling” where opposition parties insult and attack each other to get an idea of the political maturity of a country twitter users, with a high percentage negative sentiments it was deduced that people of that country lack political maturity.


Younus, Arjumand, et al. "Election trolling: analyzing sentiment in tweets during Pakistan elections 2013." Proceedings of the companion publication of the 23rd international conference on World Wide Web companion. International World Wide Web Conferences Steering Committee, 2014.

Chung, Jessica Elan, and Eni Mustafaraj. "Can collective sentiment expressed on twitter predict political elections?" AAAI. 2011.

Tumasjan, Andranik, et al. "Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment." ICWSM 10 (2010): 178-185.

O'Connor, Brendan, et al. "From tweets to polls: Linking text sentiment to public opinion time series." ICWSM 11 (2010): 122-129.

Wang, Hao, et al. "A system for real-time twitter sentiment analysis of 2012 us presidential election cycle." Proceedings of the ACL 2012 System Demonstrations. Association for Computational Linguistics, 2012.

Bilingual Roman Urdu sentiment words with weights, NUST Center of Data and Text Engineering and Mining, Sentiment Analysis for Social Network's data in Urdu,

Tool for generating word could,

Google project on sentiment analysis,

Twitter Developer blogs, 2013,

Full Text: PDF [Full Text]


  • There are currently no refbacks.

Copyright © 2013, All rights reserved.|

Creative Commons License
International Journal of Science Engineering and Advance Technology is licensed under a Creative Commons Attribution 3.0 Unported License.Based on a work at IJSEat , Permissions beyond the scope of this license may be available at