Abstract
Today lives of people have become so strenuous and hectic that they are least bothered about getting updated with the latest news. Presently, there are various sources of news ranging from newspaper to various news mobile applications. In case of newspaper, we have to read long articles and regarding news applications, we have to search for the ones which provide us credible and relevant news everyday which is also a very time-consuming task. To address this problem, a web application ‘TweetsDaily’ which fetches news in the form of tweets of two domains—Indian and Global which are posted by various news channels on their respective Twitter user timelines. The tweets of each domain are further classified into five categories, namely, Politics, Sports, Entertainment, Technology, and Miscellaneous (news related to day-to-day crimes, stocks and investment, communal disputes, terror attacks, etc.) In this paper, we represent a method for the classification of tweets in five categories of each domain. The method is a text-based classification technique based on ensemble model of different classification algorithms.
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Notes
- 1.
Gretel Liz De la Peña Sarracén [21] proposed a system based on an ensemble of five classifiers for IberEval2017 on Classification Of Spanish Election Tweets (COSET) task. F1-macro value for ensemble approach of the system is 0.5847, whereas F1-macro value for our Indian News Ensemble Classifier is 0.797.
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Gupta, D., Sharma, A., Kumar, M. (2020). TweetsDaily: Categorised News from Twitter. In: Sharma, H., Govindan, K., Poonia, R., Kumar, S., El-Medany, W. (eds) Advances in Computing and Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0222-4_5
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