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Differences in personal and professional tweets of scholars

机译:学者个人和专业推文的差异

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Purpose - The purpose of this paper is to show that there were differences in the use of Twitter by professors at AAU schools. Affordance use differed between the personal and professional tweets of professors as categorized by turkers. Framing behaviors were described that could impact the interpretation of tweets by audience members. Design/methodology/approach - A three phase research design was used that included surveys of professors, categorization of tweets by workers in Amazon's Mechanical Turk, and categorization of tweets by active professors on Twitter. Findings - There were significant differences found between professors that reported having a Twitter account, significant differences found between types of Twitter accounts (personal, professional, or both), and significant differences in the affordances used in personal and professional tweets. Framing behaviors were described that may assist altmetric researchers in distinguishing between personal and professional tweets. Research limitations/implications - The study is limited by the sample population, survey instrument, low survey response rate, and low Cohen's k. Practical implications - An overview of various affordances found in Twitter is provided and a novel use of Amazon's Mechanical Turk for the categorization of tweets is described that can be applied to future altmetric studies. Originality/value - This work utilizes a socio-technical framework integrating social and psychological theories to interpret results from the tweeting behavior of professors and the interpretation of tweets by workers in Amazon's Mechanical Turk.
机译:目的-本文的目的是表明AAU学校的教授在使用Twitter方面存在差异。在按图尔克分类的教授个人推文和专业推文中,人们对书呆子的使用方式有所不同。描述了可能影响听众对推文的解释的构架行为。设计/方法/方法-使用了一个分为三个阶段的研究设计,其中包括教授调查,亚马逊机械工公司工人的推文分类以及Twitter上活跃教授的推文分类。调查结果-报告拥有Twitter帐户的教授之间存在显着差异,在Twitter帐户类型(个人帐户,专业帐户或两者)之间存在显着差异,个人和专业推文中使用的费用也存在显着差异。描述了可能有助于高度测量研究人员区分个人和专业推文的构架行为。研究的局限性/意义-研究受到样本人口,调查工具,调查回应率低和Cohen's k低的限制。实际意义-概述了Twitter中提供的各种收费功能,并描述了Amazon Mechanical Turk在推文分类中的新颖用法,可将其应用于未来的测高研究。原创性/价值-这项工作利用社会和心理理论相结合的社会技术框架来解释教授的推特行为和亚马逊机械工公司工人的推文解释结果。

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