research-article

Representation and communication: challenges in interpreting large social media datasets

Authors:

Louise Barkhuus,

Henriette Cramer,

Barry BrownAuthors Info & Claims

CSCW '13: Proceedings of the 2013 conference on Computer supported cooperative work

Pages 357 - 362

https://doi.org/10.1145/2441776.2441817

Published: 23 February 2013 Publication History

Abstract

Online services provide a range of opportunities for understanding human behaviour through the large aggregate data sets that their operation collects. Yet the data sets they collect do not unproblematically model or mirror the world events. In this paper we use data from Foursquare, a popular location check-in service, to argue for the importance of analysing social media as a communicative rather than representational system. Drawing on logs of all Foursquare check-ins over eight weeks we highlight four features of Foursquare's use: the relationship between attendance and check-ins, event check-ins, commercial incentives to check-in, and lastly humorous check-ins These points show how large data analysis is affected by the end user uses to which social networks are put.

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Cited By

Xu WZeng PLiu BCai LSun ZLiu STang F(2024)Exploring the Built Environment Factors Influencing Town Image Using Social Media Data and Deep Learning MethodsLand10.3390/land1303029113:3(291)Online publication date: 26-Feb-2024
https://doi.org/10.3390/land13030291
Caton SHaas C(2024)Fairness in Machine Learning: A SurveyACM Computing Surveys10.1145/361686556:7(1-38)Online publication date: 9-Apr-2024
https://dl.acm.org/doi/10.1145/3616865
Lu W(2023)Streets as experienced through the body, mind, and screen: The smartphone and the pedestrian's engagement with an urban public spaceMobile Media & Communication10.1177/2050157923119730412:1(71-94)Online publication date: 6-Sep-2023
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Index Terms

Representation and communication: challenges in interpreting large social media datasets
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing systems and tools
2. Information systems
  1. World Wide Web

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Published In

cover image ACM Conferences

CSCW '13: Proceedings of the 2013 conference on Computer supported cooperative work

February 2013

1594 pages

ISBN:9781450313315

DOI:10.1145/2441776

General Chairs:
Amy Bruckman
Georgia Institute of Technology, USA
,
Scott Counts
Microsoft Research, USA
,
Program Chairs:
Cliff Lampe
University of Michigan, USA
,
Loren Terveen
University of Minnesota, USA

Copyright © 2013 ACM.

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: 23 February 2013

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February 23 - 27, 2013

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Overall Acceptance Rate 2,235 of 8,521 submissions, 26%

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Cited By

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https://doi.org/10.3390/land13030291
Caton SHaas C(2024)Fairness in Machine Learning: A SurveyACM Computing Surveys10.1145/361686556:7(1-38)Online publication date: 9-Apr-2024
https://dl.acm.org/doi/10.1145/3616865
Lu W(2023)Streets as experienced through the body, mind, and screen: The smartphone and the pedestrian's engagement with an urban public spaceMobile Media & Communication10.1177/2050157923119730412:1(71-94)Online publication date: 6-Sep-2023
https://doi.org/10.1177/20501579231197304
Kazemi AYounus AJeon MQureshi MCaton S(2023)InÉire: An Interpretable NLP Pipeline Summarizing Inclusive Policy Making Concerning Migrants in IrelandIEEE Access10.1109/ACCESS.2023.330310511(88807-88823)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3303105
Zhang ZHuang SZhang SLiu XJiang WZheng ZZhi JLong Y(2023)Online versus offline tourism emotion: uncovering the bias pattern in online tourism emotion within theme parksAsia Pacific Journal of Tourism Research10.1080/10941665.2023.229378628:11(1295-1310)Online publication date: 27-Dec-2023
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Rane S(2022)Social Media Content Analysis and Classification Using Data Mining and MLResearch Anthology on Applying Social Networking Strategies to Classrooms and Libraries10.4018/978-1-6684-7123-4.ch011(197-207)Online publication date: 8-Jul-2022
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Huang JCui YChang HObracht-Prondzyńska HKamrowska-Zaluska DLi L(2022)A city is not a tree: a multi-city study on street network and urban lifeLandscape and Urban Planning10.1016/j.landurbplan.2022.104469226(104469)Online publication date: Oct-2022
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Khera A(2021)Leveraging Data Mining Tools and Techniques to Effectively Execute Sentiment Analysis on Social Media DataInternational Journal of Research in Science and Technology10.37648/ijrst.v11i01.00411:01(34-40)Online publication date: 2021
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Kamrowska-Załuska D(2021)Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of CitiesLand10.3390/land1011120910:11(1209)Online publication date: 8-Nov-2021
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