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INTERNATIONAL JOURNAL OF INNOVATIONS IN APPLIED SCIENCES & ENGINEERINGInternational Peer Reviewed (Refereed), Open Access Research Journal (By Aryavart International University, India) E-ISSN:2454-9258 | P-ISSN:2454-809X | Estd Year: 2015 Impact Factor(2020): 4.805 | Impact Factor(2021): 5.246 |
Hardik Chaudhary, Vipul Goyal
Vol. 5, Jan-Dec 2019
Page Number: 124-128
Abstract:
The major objective of textual information retrieval is to process, search, and analyse the factual data from various applications. There are various textual contents, however, which express some subjective characteristics. Such content mainly includes the opinions, sentiments, attitudes, and emotions which contribute majorly within the fake news detection mechanisms. The fake news detection procedure has four major steps involved in it. In the initial step, the pre-processing of data is done from which the features will be extracted in the second step. The extracted features are given as input in the third step in order to classify the data for attaining fake news. With the help of existing patterns, some more patterns are generated with the help of a pattern-based technique, which is applied during the feature extraction process. This results in enhancing the accuracy of data classification. Python is used for implementing the proposed algorithm with the help of the NLTK toolbox. As per the achieved simulation results, it is seen that there is a reduction in the execution time and an enhancement inaccuracy.