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  • Open Access


    MELex: The Construction of Malay-English Sentiment Lexicon

    Nurul Husna Mahadzir1, Mohd Faizal Omar2, Mohd Nasrun Mohd Nawi3,*, Anas A. Salameh4, Kasmaruddin Che Hussin5, Abid Sohail6

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1789-1805, 2022, DOI:10.32604/cmc.2022.021131

    Abstract Currently, the sentiment analysis research in the Malaysian context lacks in terms of the availability of the sentiment lexicon. Thus, this issue is addressed in this paper in order to enhance the accuracy of sentiment analysis. In this study, a new lexicon for sentiment analysis is constructed. A detailed review of existing approaches has been conducted, and a new bilingual sentiment lexicon known as MELex (Malay-English Lexicon) has been generated. Constructing MELex involves three activities: seed words selection, polarity assignment, and synonym expansions. Our approach differs from previous works in that MELex can analyze text for the two most widely… More >

  • Open Access


    Swarming Behavior of Harris Hawks Optimizer for Arabic Opinion Mining

    Diaa Salam Abd Elminaam1,2,*, Nabil Neggaz3, Ibrahim Abdulatief Ahmed4,5, Ahmed El Sawy Abouelyazed4

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4129-4149, 2021, DOI:10.32604/cmc.2021.019047

    Abstract At present, the immense development of social networks allows generating a significant amount of textual data, which has facilitated researchers to explore the field of opinion mining. In addition, the processing of textual opinions based on the term frequency-inverse document frequency method gives rise to a dimensionality problem. This study aims to detect the nature of opinions in the Arabic language employing a swarm intelligence (SI)-based algorithm, Harris hawks algorithm, to select the most relevant terms. The experimental study has been tested on two datasets: Arabic Jordanian General Tweets and Opinion Corpus for Arabic. In terms of accuracy and number… More >

  • Open Access


    Extraction of Opinion Target Using Syntactic Rules in Urdu Text

    Toqir A. Rana1,*, Bahrooz Bakht1, Mehtab Afzal1, Natash Ali Mian2, Muhammad Waseem Iqbal3, Abbas Khalid1, Muhammad Raza Naqvi4

    Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 839-853, 2021, DOI:10.32604/iasc.2021.018572

    Abstract Opinion target or aspect extraction is the key task of aspect-based sentiment analysis. This task focuses on the extraction of targeted words or phrases against which a user has expressed his/her opinion. Although, opinion target extraction has been studied extensively in the English language domain, with notable work in other languages such as Chinese, Arabic etc., other regional languages have been neglected. One of the reasons is the lack of resources and available texts for these languages. Urdu is one, with millions of native and non-native speakers across the globe. In this paper, the Urdu language domain is focused on… More >

  • Open Access


    Enhancement of Sentiment Analysis Using Clause and Discourse Connectives

    Kumari Sheeja Saraswathy, Sobha Lalitha Devi*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1983-1999, 2021, DOI:10.32604/cmc.2021.015661

    Abstract The sentiment of a text depends on the clausal structure of the sentence and the connectives’ discourse arguments. In this work, the clause boundary, discourse argument, and syntactic and semantic information of the sentence are used to assign the text’s sentiment. The clause boundaries identify the span of the text, and the discourse connectives identify the arguments. Since the lexicon-based analysis of traditional sentiment analysis gives the wrong sentiment of the sentence, a deeper-level semantic analysis is required for the correct analysis of sentiments. Hence, in this study, explicit connectives in Malayalam are considered to identify the discourse arguments. A… More >

  • Open Access


    Building Ontology for Different Emotional Contexts and Multilingual Environment in Opinion Mining

    Wan Taoa,b, Tao Liua,b

    Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 65-72, 2018, DOI:10.1080/10798587.2016.1267243

    Abstract With the explosive growth of various social media applications, individuals and organizations are increasingly using their contents (e.g. reviews, forum discussions, blogs, micro-blogs, comments, and postings in social network sites) for decision-making. These contents are typical big data. Opinion mining or sentiment analysis focuses on how to extract emotional semantics from these big data to help users to get a better decision. That is not an easy task, because it faces many problems, such as different context may make the meaning of the same word change variously, at the same time multilingual environment restricts the full use of the analysis… More >

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