| 1 | Title of the Article | Recognizing Sentiment Prediction on Twitter Data |
| 2 | Author's name | Nishu Sethi: Department of Computer Science, Amity University, Gurgaon, Haryana, India (email: nsethi@ggn.amity.edu) |
| 3 | Author's name | Neha Bhateja, Navya Sethi, Sakshi Sinha |
| 4 | Subject | Computer Science and Engineering |
| 5 | Keyword(s) | Sentiment Analysis, Opinion Mining, Literature Review, Supervised Machine Learning |
| 6 | Abstract | Escorted by the wide spread of Internet today, people have found a new way of expressing their opinions. It is a platform with a variety of information where an individual can also view the opinions of others. This is continuously growing and becoming an important factor in decision making for various organisations, businesses and even for Politics. In this paper we have chosen the most popular social media platform i.e. Twitter for our Sentiment Analysis. Eventually, Acknowledging the opinions beyond the tweets is of great concern. The fundamental aim of Sentiment Analysis is to reason feelings and ideas of individuals. We have made data analysis with tweets related to a topic and thereby classified their polarity using different machine learning algorithms. |
| 7 | Publisher | Innovative Research Publication |
| 8 | Journal Name; vol., no. | International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-8 Issue-3 |
| 9 | Publication Date | May 2020 |
| 10 | Type | Peer-reviewed Article |
| 11 | Format | |
| 12 | Uniform Resource Identifier | https://ijircst.org/view_abstract.php?title=Recognizing-Sentiment-Prediction-on-Twitter-Data&year=2020&vol=8&primary=QVJULTM5NA== |
| 13 | Digital Object Identifier(DOI) | 10.21276/ijircst.2020.8.3.12 https://doi.org/10.21276/ijircst.2020.8.3.12 |
| 14 | Language | English |
| 15 | Page No | 102-104 |