Tweets classification and sentiment analysis for personalized tweets recommendation

Journal article


Batool, Rabia, Satti, Fahad Ahmed, Hussain, Jamil, Khan, Wajahat Ali, Khan, Adil Mehmood and Hayat, Bashir 2020. Tweets classification and sentiment analysis for personalized tweets recommendation. Complexity in Deep Neural Networks. 2020. https://doi.org/10.1155/2020/8892552
AuthorsBatool, Rabia, Satti, Fahad Ahmed, Hussain, Jamil, Khan, Wajahat Ali, Khan, Adil Mehmood and Hayat, Bashir
Abstract

Mining social network data and developing user profile from unstructured and informal data are a challenging task. The proposed research builds user profile using Twitter data which is later helpful to provide the user with personalized recommendations. Publicly available tweets are fetched and classified and sentiments expressed in tweets are extracted and normalized. This research uses domain-specific seed list to classify tweets. Semantic and syntactic analysis on tweets is performed to minimize information loss during the process of tweets classification. After precise classification and sentiment analysis, the system builds user interest-based profile by analyzing user’s post on Twitter to know about user interests. The proposed system was tested on a dataset of almost 1 million tweets and was able to classify up to 96% tweets accurately.

Keywordsdata mining; social network; Twitter
Year2020
JournalComplexity in Deep Neural Networks
Complexity
Journal citation2020
PublisherHindawi
ISSN10762787
10990526
Digital Object Identifier (DOI)https://doi.org/10.1155/2020/8892552
Web address (URL)http://hdl.handle.net/10545/625591
http://creativecommons.org/licenses/by/4.0/
hdl:10545/625591
Publication dates17 Dec 2020
Publication process dates
Deposited05 Feb 2021, 15:07
Accepted01 Dec 2020
Rights

Attribution 4.0 International

ContributorsUniversity of Derby
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