- Tytuł:
- Twitter Opinion Mining Using Sentiment Analysis
- Autorzy:
-
Maheshwari, Saumil
Shukla, Shubham
Kumari, Dazy - Powiązania:
- https://bibliotekanauki.pl/articles/1075568.pdf
- Data publikacji:
- 2019
- Wydawca:
- Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
- Tematy:
-
Naive Bayes
Opinion Mining
machine learning - Opis:
- This is very important to extract verdict or opinion of others about any product, topic or about some person. The rich sources of this opinion rich data are blogs, online review sites and social networking sites. Among the social networking sites, twitter one of such largest source of microblog has gained popularity with more than 500 million tweets per day. Because of this Twitter has become a primary source for opinion mining. Twitter messages called tweets, are much focused because of the restricted characters size of 140 characters. Social network data is one of the most effective and accurate indicators of public sentiment. In this paper, twitter data is analyzed to determine the opinion of public. Twitter data about iPhone 6 is collected for analysis using the Twitter public API which allows developers to extract tweets from twitter programmatically. In this paper, Naïve Bayes classifier is used to calculate the sentiments of tweets and compared with baseline algorithms.
- Źródło:
-
World Scientific News; 2019, 121; 73-82
2392-2192 - Pojawia się w:
- World Scientific News
- Dostawca treści:
- Biblioteka Nauki
Artykuł