Prediction of Election by Twitter

Autor: Kusum, Supriya P. Panda
Přispěvatelé: Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP)
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Popis: Nowadays social media like Twitter and Facebook etc. is one of the key players. Twitters are micro blogging sites by which users sent their opinions and views in brief. The information generated by one user can be seen by everyone. Therefore to analyze twitter sentiment can be a crucial task. For this task, we have used various approaches like novel based approach and machine learning and many other rules like context awareness are used for the detection of public opinion and prediction of results. We are studying the user tweets during elections. Meaningful tweets are collected on a definite period.The feasibility of the developed classification model is identified by our proposed work to identify the political orientation on the tweets and other user-based features. The technique for the collection of tweets in time has played an important role. When the outcome of applied technique competes with survey agencies result was published before elections result.
Databáze: OpenAIRE