Flesch-Kincaid Measure as Proxy of Socio-Economic Status on Twitter: Comparing US Senator Writing to Internet Users

IF 4.1 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Samara M. Ahmed, Adil E. Rajput, A. Sarirete, Tauseef J. Chowdhry
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引用次数: 3

Abstract

Social media gives researchers an invaluable opportunity to gain insight into different facets of human life. Researchers put a great emphasis on categorizing the socioeconomic status (SES) of individuals to help predict various findings of interest. Forum uses, hashtags and chatrooms are common tools of conversations grouping. Crowdsourcing involves gathering intelligence to group online user community based on common interest. This paper provides a mechanism to look at writings on social media and group them based on their academic background. We analyzed online forum posts from various geographical regions in the US and characterized the readability scores of users. Specifically, we collected 10,000 tweets from the members of US Senate and computed the Flesch-Kincaid readability score. Comparing the Senators’ tweets to the ones from average internet users, we note 1) US Senators’ readability based on their tweets rate is much higher, and 2) immense difference among average citizen’s score compared to those of US Senators is attributed to the wide spectrum of academic attainment.
Flesch-Kincaid测度作为Twitter上社会经济地位的代表:比较美国参议员和互联网用户的写作
社交媒体为研究人员提供了一个宝贵的机会,可以深入了解人类生活的各个方面。研究人员非常重视对个体的社会经济地位(SES)进行分类,以帮助预测各种有趣的发现。论坛、话题标签和聊天室是对话分组的常用工具。众包包括收集情报,根据共同的兴趣将在线用户社区分组。本文提供了一种机制来查看社交媒体上的文章,并根据他们的学术背景对它们进行分组。我们分析了来自美国不同地理区域的在线论坛帖子,并对用户的可读性得分进行了表征。具体来说,我们从美国参议院成员那里收集了10,000条推文,并计算了弗莱什-金凯的可读性得分。将参议员的推文与普通互联网用户的推文进行比较,我们注意到:1)基于推文率的美国参议员的可读性要高得多;2)与美国参议员相比,普通公民得分的巨大差异归因于广泛的学术成就。
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来源期刊
CiteScore
6.20
自引率
12.50%
发文量
51
审稿时长
20 months
期刊介绍: The International Journal on Semantic Web and Information Systems (IJSWIS) promotes a knowledge transfer channel where academics, practitioners, and researchers can discuss, analyze, criticize, synthesize, communicate, elaborate, and simplify the more-than-promising technology of the semantic Web in the context of information systems. The journal aims to establish value-adding knowledge transfer and personal development channels in three distinctive areas: academia, industry, and government.
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