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Using Ontology to Analyze English Comments on Social Networks

Informatika i avtomatizaciâ (Online), 2024-09, Vol.23 (5), p.1311-1338 [Peer Reviewed Journal]

ISSN: 2713-3192 ;EISSN: 2713-3206 ;DOI: 10.15622/ia.23.5.2

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  • Title:
    Using Ontology to Analyze English Comments on Social Networks
  • Author: Viet Hung, Nguyen ; Tan, Nguyen ; Thi Thuy Nga, Nguyen ; Huyen Trang, Le Thi ; Thuy Hang, Tran Thi
  • Subjects: chatbot ; deep learning ; machine learning ; ontology ; social network ; vietnam
  • Is Part Of: Informatika i avtomatizaciâ (Online), 2024-09, Vol.23 (5), p.1311-1338
  • Description: Chatbots have become interesting for many users as technology becomes more and more advanced. The need for information exchange among people through computer systems is increasing daily, raising the preference for using chatbots in most countries. Since Vietnam is such a developing country with a variety of ethnic groups, it requires much attention to the proliferation of social networks and the expansion of the cooperative economy. Regarding social networks, the inappropriate use of words in everyday life has become a significant issue. There are mixed reviews of praise and criticism on social networks; and we try to reduce the negative language use and improve the quality of using social networks language. We aim to meet users’ needs on social networks, promote economic development, and address social issues more effectively. To achieve these goals, in this paper we propose a deep learning technique using ontology knowledge mining to collect and process comments on social networks. This approach aims to enhance the user experience and facilitate the exchange of information among people by mining opinions in comments. Experimental results demonstrate that our method outperforms the conventional approach.
  • Publisher: Russian Academy of Sciences, St. Petersburg Federal Research Center
  • Language: English
  • Identifier: ISSN: 2713-3192
    EISSN: 2713-3206
    DOI: 10.15622/ia.23.5.2
  • Source: Directory of Open Access Journals
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