情感分析研究:社交媒体数据视角

Zahra Dahish, S. Miah
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引用次数: 0

摘要

情感分析已迅速用于业务决策支持。新的数据挖掘研究人员在利用社交媒体数据的同时,还没有充分了解情感分析的各种应用。因此,利用现有文献对数据挖掘和文本分析研究趋势进行整体界定是至关重要的。本研究探讨了情感分析研究在社交媒体数据转化中的应用,并通过对Scopus数据库(2018年至2022年)发表的523篇研究文章进行全面的文献计量分析,确定了相关的研究方面,以辨别内容和主题分析。研究结果表明,情绪分析的主要目的主要与创新、透明度和效率有关。我们的评论还强调了情感分析在综合社交媒体信息以调查各种特征方面的独特性,包括检测过去作者合作网络的知识领域地图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EXPLORING SENTIMENT ANALYSIS RESEARCH: A SOCIAL MEDIA DATA PERSPECTIVE
Sentiment analysis has been rapidly employed for business decision support. New data mining researchers are yet to have an adequate understanding of the various applications of sentiment analysis while utilising social media data. As a result, it is critical to define the data mining and text analytics research trend holistically using existing literature. The study explores sentiment analysis research for its application in transforming social media data and identifies relevant research aspects through a comprehensive bibliometric review of 523 research articles published in the Scopus database (between 2018 and 2022) to discern the content and thematic analysis. Findings suggested that key purposes of the sentiment analysis are mainly related to innovation, transparency, and efficiency. Our review also highlights the distinctiveness of sentiment analysis for synthesising social media information to investigate various features, including the knowledge-domain map that detects author collaboration networks in the past.
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