Recognizing Experts on Social Media: A Heuristics-Based Approach

IF 2.8 4区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
Benjamin D. Horne, Dorit Nevo, Sibel Adali
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引用次数: 7

Abstract

Knowing who is an expert on social media is a challenging yet important task, especially in a world where misleading information is commonplace and where social media is an important information source for knowledge seekers. In this paper we investigate expertise heuristics by comparing features of experts versus non-experts in big data settings. We employ a large set of features to classify experts and non-experts using data collected on two social media platform (Twitter and reddit). Our results show a good ability to predict who is an expert, especially using language-based features, validating that heuristics can be developed to differentiate experts from novices organically, based on social media use. Our results contribute to the development of expertise location and identification systems as well as our understanding on how experts present themselves on social media.
识别社会媒体上的专家:一种基于启发式的方法
了解谁是社交媒体专家是一项具有挑战性但又很重要的任务,尤其是在一个误导性信息司空见惯的世界里,社交媒体是求知者的重要信息来源。在本文中,我们通过比较大数据环境中专家与非专家的特征来研究专家启发式。我们使用从两个社交媒体平台(Twitter和reddit)收集的数据,采用大量的特征来对专家和非专家进行分类。我们的结果显示了一个很好的预测谁是专家的能力,特别是使用基于语言的特征,验证了基于社交媒体使用的启发式方法可以有机地区分专家和新手。我们的研究结果有助于专业知识定位和识别系统的发展,以及我们对专家如何在社交媒体上展示自己的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Data Base for Advances in Information Systems
Data Base for Advances in Information Systems INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
3.60
自引率
7.10%
发文量
18
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