Data Mining and Knowledge Engineering

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Political Bias Recognition using Tweets


Affiliations
1 Department of Computer Science and Engineering, Rajarajeswari College of Engineering, Bangalore, India
2 Department of Computer Science and Engineering, Rajarajeswari College of Engineering, Bangalore, India
     

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Social media is frequently used to convey one‟s thoughts and views regarding business, products, services, politics, and other topics. The scientific community has put up a significant effort to develop systems for analyzing, structuring and processing enormous volumes of online reviews in social media. In micro - blogging texts, a variety of Sentiment Analysis (SA) approaches are employed to extract the polarity (positive, negative, mixed/neutral) that users experience. In this regard, Twitter™ has grown in popularity as a popular micro-blogging service where users may express themselves in as few as 280 characters. This brevity aids scientists in grasping the gist and insights of a person's "opinion". Using Machine Learning, we can discern a political party's popularity using this data; this helps political parties acquire a better understanding of their "image," and it helps the average person identify the party that has a greater probability of winning an election or assist him choose the best.

Keywords

Sentiment Analysis, Machine Learning, Micro Blogging
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Abstract Views: 130

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  • Political Bias Recognition using Tweets

Abstract Views: 130  |  PDF Views: 0

Authors

R Nishanth
Department of Computer Science and Engineering, Rajarajeswari College of Engineering, Bangalore, India
Manish Seena Devadiga
Department of Computer Science and Engineering, Rajarajeswari College of Engineering, Bangalore, India

Abstract


Social media is frequently used to convey one‟s thoughts and views regarding business, products, services, politics, and other topics. The scientific community has put up a significant effort to develop systems for analyzing, structuring and processing enormous volumes of online reviews in social media. In micro - blogging texts, a variety of Sentiment Analysis (SA) approaches are employed to extract the polarity (positive, negative, mixed/neutral) that users experience. In this regard, Twitter™ has grown in popularity as a popular micro-blogging service where users may express themselves in as few as 280 characters. This brevity aids scientists in grasping the gist and insights of a person's "opinion". Using Machine Learning, we can discern a political party's popularity using this data; this helps political parties acquire a better understanding of their "image," and it helps the average person identify the party that has a greater probability of winning an election or assist him choose the best.

Keywords


Sentiment Analysis, Machine Learning, Micro Blogging

References