Python代码和Twitter的说明性危机管理数据

IF 0.4 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS African Journal of Information Systems Pub Date : 2022-06-21 DOI:10.2308/isys-2022-011
Y. Wang, T. Wang
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引用次数: 0

摘要

本文介绍了Python代码和来自Twitter的说明性危机管理数据。该代码包括Twitter数据收集和三种易于使用的机器学习算法。三种机器学习算法生成情绪度量,从推文中提取主题,并比较不同时间主题的相似性。代码和说明性数据将对有兴趣使用Twitter数据分析广泛的公众看法和反应(如StockTwits活动)的研究人员开放;重大事件,如宣布投资决定或安全漏洞;#地球日#等公共运动;以及入侵乌克兰等重大全球事件。更好地理解代码和数据集将使该领域的研究人员能够进行更广泛的研究,充分利用这一丰富的数据源来捕捉公众的看法。
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Python Code and Illustrative Crisis Management Data from Twitter
This paper presents the Python code and illustrative crisis management data from Twitter. The code includes Twitter data collection and three machine learning algorithms that are readily usable. Three machine learning algorithms generate sentiment measures, extract topics from the tweets and, compare the similarity of topics across time. The code and the illustrative data will be accessible to researchers that are interested in using Twitter data to analyze a wide range of public perceptions and responses such as StockTwits activity; firm events such as the announcement of investment decisions or security breaches; public movements such as #earthday; and significant global events such as the invasion of Ukraine. A better understanding of the code and datasets will enable researchers in this field to engage in more extensive studies that fully utilize this rich data source to capture public perceptions.
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来源期刊
African Journal of Information Systems
African Journal of Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
14.30%
发文量
0
审稿时长
30 weeks
期刊最新文献
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