情报研究

Altmetrics中的社交媒体事件分析

  • 刘晓娟 ,
  • 韦娱 ,
  • 赵卓婧
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  • 北京师范大学政府管理学院 北京 100875
刘晓娟(ORCID:0000-0002-5727-733X),教授,博士,硕士生导师,E-mail:lxj_2007@bnu.edu.cn;韦娱(ORCID:0000-0003-2377-7683),硕士研究生;赵卓婧(ORCID:0000-0003-3009-037X),硕士研究生。

收稿日期: 2019-01-25

  修回日期: 2019-04-14

  网络出版日期: 2019-10-05

基金资助

本文系国家社会科学基金项目"社交媒体视域下科研评价的理论与方法研究"(项目编号:17BTQ070)研究成果之一。

Analysis of Social Media Events in Altmetrics

  • Liu Xiaojuan ,
  • Wei Yu ,
  • Zhao Zhuojing
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  • School of Government, Beijing Normal University, Beijing 100875

Received date: 2019-01-25

  Revised date: 2019-04-14

  Online published: 2019-10-05

Supported by

 

摘要

[目的/意义] 为明确社交媒体中学术成果被关注、传播和利用等行为的内涵与意义,对已使用与可挖掘的altmetrics指标进行深度剖析。[方法/过程] 从事件本体视角出发,对社交媒体中与学术成果相关的行为进行抽象,从事件的主体、客体、产出、类型、动机、时间、地点和来源出发,构建社交媒体事件模型,并以Mendeley与Twitter为例进行社交媒体事件的深层次分析。[结果/结论] 目前altmetrics聚合器所提供的指标仅来自于社交媒体上的部分事件,通过对社交媒体事件及其各要素的剖析,发现未来应该纳入其他同样具有学术评价价值的指标,如文献被加入的Mendeley讨论组数量、推文点赞数等。指标利用中需要根据事件的各个要素去评定各指标在不同学术评价情境中的适用程度,同时也要考虑数据采集的方法、频率和限制条件等,以保证指标值的准确性和科学性。

本文引用格式

刘晓娟 , 韦娱 , 赵卓婧 . Altmetrics中的社交媒体事件分析[J]. 图书情报工作, 2019 , 63(19) : 112 -118 . DOI: 10.13266/j.issn.0252-3116.2019.19.011

Abstract

[Purpose/significance] In order to clarify the connotation and significance of the attention, dissemination and utilization of academic achievements in social media, to make a deep analysis of the altmetrics indicators that have been used and can be mined.[Method/process] From the perspective of event ontology, the acts related to academic achievements in social media are abstracted. Starting from the subject, object, product, type, motivation, time, place and resource of the event, the event model of social media is constructed. And the deep analysis of social media events is carried out with Mendeley and Twitter as examples.[Result/conclusion] At present, altmetrics aggregators only provide indicators from some social media events. Through the analysis of social media events and their elements, it is found that some other indicators with academic evaluation value should be included in evaluation system in the future, such as Mendeley group_count, Twitter favorite_count and so on. When using these indicators, it is necessary to evaluate the applicability of indicators in different academic evaluation contexts according to the elements of events. Meanwhile, the methods, frequencies and limitations of data acquisition should be taken into account to ensure the accuracy and scientificity of the indicators.

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