公民对GST的情绪--基于Twitter数据的时空分析
Citizens' Emotion on GST: A Spatio-Temporal Analysis over Twitter Data
摘要：
人们可能不会近在咫尺，但他们仍然是-凭借社会网络。社交网络在许多方面改变了人们的生活。人们可以在各种平台上表达他们的观点，意见和生活经历，无论是Twitter，Facebook还是任何其他媒体。此类活动包括审查产品或服务、传达对政治玩笑的看法、预测股价或对非货币化或商品及服务税等政府政策提供反馈。这些社交平台可以用来调查公众产生的情感曲线的见解。这种分析可以使产品更好，预测未来的前景，也可以更好地执行公共政策。这种对情感分析的研究正在迅速增加。在这篇研究论文中，我们分别对1，42，508和58，613条推文进行了时间分析和空间分析，这些推文是在2017年7月4日至2017年7月25日的GST实施期间发布的。这些推文是使用Twitter流媒体API收集的。一个著名的词汇，加拿大国家研究委员会（NRC）情感词汇被用于意见挖掘，表现出八种基本情感的混合，即喜悦，信任，预期，惊讶，恐惧悲伤，愤怒，厌恶和两种情感，即积极和消极的6,554个单词。
英文摘要：
People might not be close-at-hand but they still are - by virtue of the social network. The social network has transformed lives in many ways. People can express their views, opinions and life experiences on various platforms be it Twitter, Facebook or any other medium there is. Such events constitute of reviewing a product or service, conveying views on political banters, predicting share prices or giving feedback on the government policies like Demonetization or GST. These social platforms can be used to investigate the insights of the emotional curve that the general public is generating. This kind of analysis can help make a product better, predict the future prospects and also to implement the public policies in a better way. Such kind of research on sentiment analysis is increasing rapidly. In this research paper, we have performed temporal analysis and spatial analysis on 1,42,508 and 58,613 tweets respectively and these tweets were posted during the post-GST implementation period from July 04, 2017 to July 25, 2017. The tweets were collected using the Twitter streaming API. A well-known lexicon, National Research Council Canada (NRC) emotion Lexicon is used for opinion mining that exhibits a blend of eight basic emotions i.e. joy, trust, anticipation, surprise, fear sadness, anger, disgust and two sentiments i.e. positive and negative for 6,554 words.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
