Social media platforms are thriving nowadays, so a huge volume of data is produced. As it includes brief and clear statements, millions of people post their thoughts on microblogging sites every day. This paper represents and analyze the capacity of diverse strategies to volumetric, delicate, and social networks to predict critical opinions from online social networking sites. In the exploration of certain searching for relevant, the thoughts of people play a crucial role. Social media becomes a good outlet since the last decades to share the opinions globally. Sentiment analysis as well as opinion mining is a tool that is used to extract the opinions or thoughts of the common public. An occurrence in one place, be it economic, political, or social, may trigger large-scale chain public reaction across many other sites in an increasingly interconnected world. This study demonstrates the evaluation of sentiment analysis techniques using social media contents and creating the association between subjectivity with herd behavior and clustering coefficient as well as tries to predict the election result (2021 election in West Bengal). This is an implementation of sentiment analysis targeted at estimating the results of an upcoming election by assessing the public's opinion across social media. This paper also has a short discussion section on the usefulness of the idea in other fields.
翻译:如今,社交媒体平台蓬勃发展,因此产生了大量数据。由于它包含简短和清晰的声明,数百万人每天在微博客网站上发表他们的想法。本文代表并分析了从在线社交网站预测批评意见的量子、微妙和社会网络的各种战略的能力。在探索某些相关内容的过程中,人们的想法起着关键作用。社交媒体自过去几十年以来成为全球交流观点的良好渠道。情感分析以及见解挖掘是用来提取公众意见或想法的工具。在一个地方,无论是经济、政治还是社会,都可能在日益相互关联的世界中引发许多其他网站的大规模连锁公众反应。这份研究还展示了对情绪分析技术的评价,利用社交媒体的内容,在主题与女性行为和组合系数之间建立联系,并试图预测选举结果(西孟加拉邦2021年选举 ) 。这是对情绪分析的一种实施,目的是通过评估社会媒体的公众意见来估计即将举行的选举结果。本文还简短地讨论了其他领域观点的实用性。