4 results for “Twitter Clustering”

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Research ArticleOpen accessIn the keywordsA Hierarchical Clustering Approach for DBpedia based Contextual Information of TweetsVenkatesha Maravanthe, Prasanth Ganesh Rao, Anita Kanavalli et al.The past decade has seen a tremendous increase in the adoption of Social Web leading to the generation of enormous amount of user data every day. The constant stream of tweets with an innate complex sentimental and contextual nature makes searching for relevant information a herculean task. Multiple applications use Twitter for various domain sensitive and analytical use-cases. This paper … …Journal of Computer Science, Vol. 16, Issue 3 · 25 Mar 2020 · 7,246 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsCLUSTERING TWEETS USING CELLULAR GENETIC ALGORITHMAmr Adel, Essam ElFakharany, Amr BadrAs the popularity of Twitter continues to increase rapidly, it is extremely necessary to analyze the huge amount of data that Twitter users generate. A popular method of tweet analysis is clustering. Because most tweets are textual, this study focuses on clustering tweets based on their textual content similarity. This study presents tweet clustering using cellular genetic algorithm cGA. The … …Journal of Computer Science, Vol. 10, Issue 7 · 16 Jun 2014 · 7,915 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsMining of Social Media on Covid-19 Big Data Infodemic in IndonesiaFaisal Binsar, Tuga MauritsiusCovid-19 is an unprecedented disaster that is still difficult to contain. During the pandemic, there were a lot of cases that were reported to increase exponentially. In this situation, the dissemination of messages and information was very important. The social media platform has contributed as a channel of communication with unprecedented speed. However, the uncontrolled and irresponsible dissemination of information … …Journal of Computer Science, Vol. 16, Issue 11 · 16 Nov 2020 · 7,533 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Sentiment-Aware Hybrid Ensemble Clustering Framework for Social Network Content Analysis and Community DiscoveryDhimesh Pravinbhai Parmar, Paresh TannaSocial media stages produce huge volumes of short, familiar, and sentiment-rich content that offerings significant encounter for community discovery and thematic analysis. Traditional clustering approach struggle with sparsity, noise, and limited surroundings information present in such texts. To address these limitations, this study introduces a sentiment-aware hybrid ensemble clustering framework designed openly for social network content analysis. The planned method … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,271 accessesView PDF Cite