DocumentCode :
116643
Title :
Prediction and analysis of Pakistan election 2013 based on sentiment analysis
Author :
Razzaq, Muhammad Asif ; Qamar, Ali Mustafa ; Bilal, Hafiz Syed Muhammad
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci. (SEECS), Nat. Univ. of Sci. & Technol. (NUST), Islamabad, Pakistan
fYear :
2014
fDate :
17-20 Aug. 2014
Firstpage :
700
Lastpage :
703
Abstract :
The significance of social media has already been proven in provoking transformation of public opinion for developed countries in improving democratic process of elections. On the contrary, developing countries lacking basic necessities of life possess monopolistic electoral system in which candidates are elected based on tribes, family backgrounds, or landlord influences. They extort voters to cast votes against their promises for the provision of basic needs. Similarly voters also poll votes for personal interests being unaware of party manifesto or national interest. These issues can be addressed by social media, resulting as ongoing process of improvement for presently adopted electoral procedures. People of Pakistan utilized social media to garner support and campaign for political parties in General Elections 2013. Political leaders, parties, and people of Pakistan disseminated party´s agenda and advocacy of party´s ideology on Twitter without much campaigning cost. To study effectiveness of social media inferred from individual´s political behavior, large scale analysis, sentiment detection & tweet classification was done in order to classify, predict and forecast election results. The experimental results depicts that social media content can be used as an effective indicator for capturing political behaviors of different parties Positive, negative and neutral behavior of the party followers as well as party´s campaign impact can be predicted from the analysis. The analytical findings proved to be having considerable correspondence with actual results as published by Election Commission of Pakistan..
Keywords :
behavioural sciences computing; government data processing; natural language processing; pattern classification; social networking (online); text analysis; Pakistan election 2013 analysis; Pakistan election 2013 prediction; Twitter; election democratic process improvement; electoral procedures; general elections 2013; large scale analysis; monopolistic electoral system; national interest; party follower negative behavior; party follower neutral behavior; party follower positive behavior; party ideology advocacy; party manifesto; political behavior capture; political parties; poll votes; public opinion transformation; sentiment analysis; sentiment detection; social media content; tweet classification; Accuracy; Conferences; Media; Nominations and elections; Sentiment analysis; Twitter; Prediction; Sentiment Analysis; Twitter Forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/ASONAM.2014.6921662
Filename :
6921662
Link To Document :
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