Analyzing Hybrid C۴.۵ Algorithm for Sentiment Extraction over Lexical and Semantic Interpretation
- سال انتشار: 1402
- محل انتشار: فصلنامه مدیریت فناوری اطلاعات، دوره: 15، شماره: 0
- کد COI اختصاصی: JR_JITM-15-0_004
- زبان مقاله: انگلیسی
- تعداد مشاهده: 151
نویسندگان
Research Scholar, Department of Computer Science and Engineering, Hemvati Nandan Bahuguna Garhwal University (A Central University), Srinagar Garhwal, Uttarakhand, India.
Professor, Head, Department of Computer Science and Engineering, Hemvati Nandan Bahuguna Garhwal University (A Central University), Srinagar Garhwal, Uttarakhand, India.
School of Computer and Systems Sciences, JNU New Delhi, India.
Department of Computer Science and Engineering, Gaya College of Engineering, Gaya.
چکیده
Internet-based social channels have turned into an important information repository for many people to get an idea about current trends and events happening around the world. As a result of Abundance of raw information on these social media platforms, it has become a crucial platform for businesses and individuals to make decisions based on social media analytics. The ever-expanding volume of online data available on the global network necessitates the use of specialized techniques and methods to effectively analyse and utilize this vast amount of information. This study's objective is to comprehend the textual information at the Lexical and Semantic level and to extract sentiments from this information in the most accurate way possible. To achieve this, the paper proposes to cluster semantically related words by evaluating their lexical similarity with respect to feature and sequence vectors. The proposed method utilizes Natural Language Processing, semantic and lexical clustering and hybrid C۴.۵ algorithm to extract six subcategories of emotions over three classes of sentiments based on word-based analysis of text. The proposed approach has yielded superior results with seven existing approaches in terms of parametric values, with an accuracy of ۰.۹۶, precision of ۰.۹۲, sensitivity of ۰.۹۴, and an f۱-score of ۰.۹۲.کلیدواژه ها
Hybrid C۴.۵, Lexical Analysis, Machine learning, Semantic Analysis, Sentiment analysis, Social Media Dataاطلاعات بیشتر در مورد COI
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