Tweet Sentiment Analysis for 2019 Indonesia Presidential Election Results using Various Classification Algorithms

被引：0

作者：

Wenando, Febby Apri ^{[1
]}

Hayami, Regiolina ^{[1
]}

Bakaruddin ^{[2
]}

Novermahakim, Ali Yunda ^{[3
]}

机构：

[1] Univ Muhammadiyah Riau, Informat Engn, Kota Pekanbaru, Riau, Indonesia

[2] Univ Muhammadiyah Riau, Management, Kota Pekanbaru, Riau, Indonesia

[3] Univ Islam Riau, Informat Engn, Kota Pekanbaru, Riau, Indonesia

来源：

2020 1ST INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY, ADVANCED MECHANICAL AND ELECTRICAL ENGINEERING (ICITAMEE 2020) | 2020年

关键词：

Presidential Election; sentiment analysis; Text mining; twitter;

D O I：

10.1109/ICITAMEE50454.2020.9398513

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The Presidential general election on 2019 became one of the most popular topics on twitter nowdays. Sentiment analysis over Twitter offers people a effective way to measure the public's feelings towards their party and politicians. The society give their opinion about the pair of candidates that they are support through the social media. This paper addresses the sentiment analysis on Twitter data, The dataset was used based on the tweet on the @jokowi twitter account. The retrieval of data by using the Tweepy library with the Python 2.7 programming language. We utilized few of machine learning algorithm to build our classifier and classified the test data as positive and negative sentiment for the training dataset. This research proposes the weighting word method Unigram, Bigram, Trigram, N-Gram (1-2) and N-Gram (1-3) combined with several machine learning algorithms to compare the best algorithm.

引用

页码：279 / 282

页数：4

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