Hybrid Perception Analysis of World Leaders in Reddit using Sentiment Analysis

Varun Rishwandh Sekar, Thuhin Khanna Rajesh Kannan, Suraj N, P. Vijay
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Abstract

Natural Language Processing (NLP) is the branch of Artificial Intelligence that deals with the interpretation of human speech. NLP is a vast area of study that is continually being developed each day, with active research happening worldwide. The development of NLP algorithms is of utmost importance to the advancements in the field of Artificial Intelligence. With the increasing popularity of social media and the number of hours spent on social media multiplying, people share their opinion on a wide range of topics and issues. This sudden burst of data generated by social media platforms contains a massive potential when combined with state-of-the-art NLP models, it can be leveraged to our advantage. This work builds a dataset of user comments on the top posts about political leaders on Reddit, using Reddit’s API. On Reddit, extensive discussions on various topics occur daily. The end goal of this work is to rank the chosen world leaders based on their likability. To find the general likability of a public personality, we try to classify the comments collected from Reddit using Sentiment Analysis. This paper employs state-of-the-art NLP algorithms such as Flair, DistilBERT, and Text Blob Analysis, and combines the results to get a better final rank of the world leaders.
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使用情感分析的Reddit世界领导人的混合感知分析
自然语言处理(NLP)是人工智能的一个分支,它处理人类语言的解释。NLP是一个广阔的研究领域,每天都在不断发展,全世界都在进行积极的研究。自然语言处理算法的发展对人工智能领域的进步至关重要。随着社交媒体的日益普及和花在社交媒体上的时间成倍增加,人们就广泛的话题和问题分享他们的观点。社交媒体平台产生的突然爆发的数据包含了巨大的潜力,当与最先进的自然语言处理模型相结合时,它可以被利用为我们的优势。这项工作使用Reddit的API,建立了Reddit上关于政治领导人的热门帖子的用户评论数据集。在Reddit上,每天都有关于各种话题的广泛讨论。这项工作的最终目标是根据他们的受欢迎程度对选定的世界领导人进行排名。为了找出公众人物的总体可爱度,我们尝试使用情感分析对从Reddit收集的评论进行分类。本文采用了最先进的自然语言处理算法,如Flair、DistilBERT和Text Blob Analysis,并将结果结合起来,以获得更好的世界领导者的最终排名。
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