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Finding and assessing social media information sources in the context of journalism

Published: 05 May 2012 Publication History

Abstract

Social media is already a fixture for reporting for many journalists, especially around breaking news events where non-professionals may already be on the scene to share an eyewitness report, photo, or video of the event. At the same time, the huge amount of content posted in conjunction with such events serves as a challenge to finding interesting and trustworthy sources in the din of the stream. In this paper we develop and investigate new methods for filtering and assessing the verity of sources found through social media by journalists. We take a human centered design approach to developing a system, SRSR ("Seriously Rapid Source Review"), informed by journalistic practices and knowledge of information production in events. We then used the system, together with a realistic reporting scenario, to evaluate the filtering and visual cue features that we developed. Our evaluation offers insights into social media information sourcing practices and challenges, and highlights the role technology can play in the solution.

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    cover image ACM Conferences
    CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
    May 2012
    3276 pages
    ISBN:9781450310154
    DOI:10.1145/2207676
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 05 May 2012

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    Author Tags

    1. computational journalism
    2. news events
    3. social media

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    • (2024)Rumor Detection on Twitter using tweet and user featuresSignal and Data Processing10.61186/jsdp.21.2.1521:2(15-28)Online publication date: 1-Oct-2024
    • (2024)HAPI: An efficient Hybrid Feature Engineering-based Approach for Propaganda Identification in social mediaPLOS ONE10.1371/journal.pone.030258319:7(e0302583)Online publication date: 10-Jul-2024
    • (2024)Fake news detection: Taxonomy and comparative studyInformation Fusion10.1016/j.inffus.2023.102140103(102140)Online publication date: Mar-2024
    • (2024)Understanding Multi-platform Social Media Aggregators: A Design and Development Case Study with BTS-DASHSocial Computing and Social Media10.1007/978-3-031-61281-7_2(19-43)Online publication date: 29-Jun-2024
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    • (2023)Tweet Trajectory and AMPS-based Contextual Cues can Help Users Identify MisinformationProceedings of the ACM on Human-Computer Interaction10.1145/35795367:CSCW1(1-27)Online publication date: 16-Apr-2023
    • (2023)AngleKindling: Supporting Journalistic Angle Ideation with Large Language ModelsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580907(1-16)Online publication date: 19-Apr-2023
    • (2023)Visual User-Generated Content Verification in Journalism: An OverviewIEEE Access10.1109/ACCESS.2023.323699311(6748-6769)Online publication date: 2023
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