Building the 'Truthmeter': Training algorithms to help journalists assess the credibility of social media sources

被引:30
作者
Fletcher, Richard [1 ]
Schifferes, Steve [2 ]
Thurman, Neil [3 ]
机构
[1] Univ Oxford, Reuters Inst Study Journalism, Oxford, England
[2] City Univ London, Financial Journalism, London, England
[3] Ludwig Maximilians Univ Munchen, Munich, Germany
来源
CONVERGENCE-THE INTERNATIONAL JOURNAL OF RESEARCH INTO NEW MEDIA TECHNOLOGIES | 2020年 / 26卷 / 01期
关键词
Algorithms; computational journalism; credibility; fake news; journalistic practice; news; social media; sourcing practices; verification; NEWS SOURCE; INFORMATION; TWITTER; BRITISH; TWEETS; DUTCH; TOOL; AGE;
D O I
10.1177/1354856517714955
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
Social media is now used as an information source in many different contexts. For professional journalists, the use of social media for news production creates new challenges for the verification process. This article describes the development and evaluation of the 'Truthmeter' - a tool that automatically scores the journalistic credibility of social media contributors in order to inform overall credibility assessments. The Truthmeter was evaluated using a three-stage process that used both qualitative and quantitative methods, consisting of (1) obtaining a ground truth, (2) building a description of existing practices and (3) calibration, modification and testing. As a result of the evaluation process, which could be generalized and applied in other contexts, the Truthmeter produced credibility scores that were closely aligned with those of trainee journalists. Substantively, the evaluation also highlighted the importance of 'relational' credibility assessments, where credibility may be attributed based on networked connections to other credible contributors.
引用
收藏
页码:19 / 34
页数:16
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