IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v57y2023i6d10.1007_s11135-023-01615-w.html
   My bibliography  Save this article

Sampling Twitter users for social science research: evidence from a systematic review of the literature

Author

Listed:
  • Paula Vicente

    (ISCTE-Instituto Universitário de Lisboa)

Abstract

All social media platforms can be used to conduct social science research, but Twitter is the most popular as it provides its data via several Application Programming Interfaces, which allows qualitative and quantitative research to be conducted with its members. As Twitter is a huge universe, both in number of users and amount of data, sampling is generally required when using it for research purposes. Researchers only recently began to question whether tweet-level sampling—in which the tweet is the sampling unit—should be replaced by user-level sampling—in which the user is the sampling unit. The major rationale for this shift is that tweet-level sampling does not consider the fact that some core discussants on Twitter are much more active tweeters than other less active users, thus causing a sample biased towards the more active users. The knowledge on how to select representative samples of users in the Twitterverse is still insufficient despite its relevance for reliable and valid research outcomes. This paper contributes to this topic by presenting a systematic quantitative literature review of sampling plans designed and executed in the context of social science research in Twitter, including: (1) the definition of the target populations, (2) the sampling frames used to support sample selection, (3) the sampling methods used to obtain samples of Twitter users, (4) how data is collected from Twitter users, (5) the size of the samples, and (6) how research validity is addressed. This review can be a methodological guide for professionals and academics who want to conduct social science research involving Twitter users and the Twitterverse.

Suggested Citation

  • Paula Vicente, 2023. "Sampling Twitter users for social science research: evidence from a systematic review of the literature," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(6), pages 5449-5489, December.
    • Handle: RePEc:spr:qualqt:v:57:y:2023:i:6:d:10.1007_s11135-023-01615-w
    DOI: 10.1007/s11135-023-01615-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-023-01615-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11135-023-01615-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kristen Olson, 2013. "Paradata for Nonresponse Adjustment," The ANNALS of the American Academy of Political and Social Science, , vol. 645(1), pages 142-170, January.
    2. Yu, Houqiang & Xiao, Tingting & Xu, Shenmeng & Wang, Yuefen, 2019. "Who posts scientific tweets? An investigation into the productivity, locations, and identities of scientific tweeters," Journal of Informetrics, Elsevier, vol. 13(3), pages 841-855.
    3. Darja Reuschke & Jed Long & Nick Bennett, 2021. "Locating creativity in the city using Twitter data," Environment and Planning B, , vol. 48(9), pages 2607-2622, November.
    4. Fischer, Eileen & Reuber, A. Rebecca, 2011. "Social interaction via new social media: (How) can interactions on Twitter affect effectual thinking and behavior?," Journal of Business Venturing, Elsevier, vol. 26(1), pages 1-18, January.
    5. Emilio Ferrara & Zeyao Yang, 2015. "Measuring Emotional Contagion in Social Media," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-14, November.
    6. Moshkovitz, Karin & Hayat, Tsahi, 2021. "The rich get richer: Extroverts' social capital on twitter," Technology in Society, Elsevier, vol. 65(C).
    7. Rachel Sharples, 2021. "Disrupting State Spaces: Asylum Seekers in Australia’s Offshore Detention Centres," Social Sciences, MDPI, vol. 10(3), pages 1-16, March.
    8. Tomu Tominaga & Yoshinori Hijikata & Joseph A. Konstan, 2018. "How self-disclosure in Twitter profiles relate to anonymity consciousness and usage objectives: a cross-cultural study," Journal of Computational Social Science, Springer, vol. 1(2), pages 391-435, September.
    9. Schaarschmidt, Mario & Könsgen, Raoul, 2020. "Good citizen, good ambassador? Linking employees' reputation perceptions with supportive behavior on Twitter," Journal of Business Research, Elsevier, vol. 117(C), pages 754-763.
    10. Han, Sehee & Min, Jinyoung & Lee, Heeseok, 2015. "Antecedents of social presence and gratification of social connection needs in SNS: A study of Twitter users and their mobile and non-mobile usage," International Journal of Information Management, Elsevier, vol. 35(4), pages 459-471.
    11. Kristina Lerman & Luciano G. Marin & Megha Arora & Lucas H. Costa Lima & Emilio Ferrara & David Garcia, 2018. "Language, demographics, emotions, and the structure of online social networks," Journal of Computational Social Science, Springer, vol. 1(1), pages 209-225, January.
    12. Gregory Eady & Jonathan Nagler & Andy Guess & Jan Zilinsky & Joshua A. Tucker, 2019. "How Many People Live in Political Bubbles on Social Media? Evidence From Linked Survey and Twitter Data," SAGE Open, , vol. 9(1), pages 21582440198, February.
    13. Mohammed, Abdulalem & Ferraris, Alberto, 2021. "Factors influencing user participation in social media: Evidence from twitter usage during COVID-19 pandemic in Saudi Arabia," Technology in Society, Elsevier, vol. 66(C).
    14. Tao Lu & Aimee L. Franklin, 2018. "A Protocol for Identifying and Sampling From Proxy Populations," Social Science Quarterly, Southwestern Social Science Association, vol. 99(4), pages 1535-1546, December.
    15. Hino, Airo & Fahey, Robert A., 2019. "Representing the Twittersphere: Archiving a representative sample of Twitter data under resource constraints," International Journal of Information Management, Elsevier, vol. 48(C), pages 175-184.
    16. Eszter Hargittai, 2015. "Is Bigger Always Better? Potential Biases of Big Data Derived from Social Network Sites," The ANNALS of the American Academy of Political and Social Science, , vol. 659(1), pages 63-76, May.
    17. Samuel-Azran, Tal & Hayat, Tsahi (Zack), 2020. "The geography of the Arab public sphere on Twitter," Technology in Society, Elsevier, vol. 62(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thomas Fujiwara & Karsten Müller & Carlo Schwarz, 2021. "The Effect of Social Media on Elections: Evidence from the United States," NBER Working Papers 28849, National Bureau of Economic Research, Inc.
    2. Thomas Fujiwara & Karsten Müller & Carlo Schwarz, 2024. "The Effect of Social Media on Elections: Evidence from The United States," Journal of the European Economic Association, European Economic Association, vol. 22(3), pages 1495-1539.
    3. Fan, Rui & Xu, Ke & Zhao, Jichang, 2018. "An agent-based model for emotion contagion and competition in online social media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 245-259.
    4. Karunakaran, Arvind & Orlikowski, Wanda J. & Scott, Susan V., 2022. "Crowd-based accountability: examining how social media commentary reconfigures organizational accountability," LSE Research Online Documents on Economics 114401, London School of Economics and Political Science, LSE Library.
    5. repec:osf:osfxxx:x6vda_v1 is not listed on IDEAS
    6. Khan, Nawab Ali & Azhar, Mohd & Rahman, Mohd Nayyer & Akhtar, Mohd Junaid, 2022. "Scale development and validation for usage of social networking sites during COVID-19," Technology in Society, Elsevier, vol. 70(C).
    7. Mochon, Daniel & Schwartz, Janet, 2024. "The confrontation effect: When users engage more with ideology-inconsistent content online," Organizational Behavior and Human Decision Processes, Elsevier, vol. 185(C).
    8. Guohui Song & Yongbin Wang, 2021. "Mainstream Value Information Push Strategy on Chinese Aggregation News Platform: Evolution, Modelling and Analysis," Sustainability, MDPI, vol. 13(19), pages 1-17, October.
    9. Rydén, Pernille & Ringberg, Torsten & Wilke, Ricky, 2015. "How Managers' Shared Mental Models of Business–Customer Interactions Create Different Sensemaking of Social Media," Journal of Interactive Marketing, Elsevier, vol. 31(C), pages 1-16.
    10. Ahmed Abouzeid & Ole-Christoffer Granmo & Morten Goodwin & Christian Webersik, 2024. "Towards misinformation mitigation on social media: novel user activity representation for modeling societal acceptance," Journal of Computational Social Science, Springer, vol. 7(1), pages 741-776, April.
    11. Benjamin Appiah Osei & Ama Nyenkua Abenyin, 2016. "Applying the Engell–Kollat–Blackwell model in understanding international tourists’ use of social media for travel decision to Ghana," Information Technology & Tourism, Springer, vol. 16(3), pages 265-284, September.
    12. Langley, David J. & Hoeve, Maarten C. & Ortt, J. Roland & Pals, Nico & van der Vecht, Bob, 2014. "Patterns of Herding and their Occurrence in an Online Setting," Journal of Interactive Marketing, Elsevier, vol. 28(1), pages 16-25.
    13. AFAWUBO, Komivi & NOGLO, Yawo Agbényégan, 2022. "ICT and entrepreneurship: A comparative analysis of developing, emerging and developed countries," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    14. Folajimi Ashiru & Franklin Nakpodia & Jacqueline J You, 2023. "Adapting emerging digital communication technologies for resilience: evidence from Nigerian SMEs," Annals of Operations Research, Springer, vol. 327(2), pages 795-823, August.
    15. Alotaibi, Norah Basheer & Mukred, Muaadh, 2022. "Factors affecting the cyber violence behavior among Saudi youth and its relation with the suiciding: A descriptive study on university students in Riyadh city of KSA," Technology in Society, Elsevier, vol. 68(C).
    16. Smith, Claudia & Smith, J. Brock & Shaw, Eleanor, 2017. "Embracing digital networks: Entrepreneurs' social capital online," Journal of Business Venturing, Elsevier, vol. 32(1), pages 18-34.
    17. Rippa, Pierluigi & Secundo, Giustina, 2019. "Digital academic entrepreneurship: The potential of digital technologies on academic entrepreneurship," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 900-911.
    18. Plé, Loïc & Demangeot, Catherine, 2020. "Social contagion of online and offline deviant behaviors and its value outcomes: The case of tourism ecosystems," Journal of Business Research, Elsevier, vol. 117(C), pages 886-896.
    19. Wenting Yu & Zhicong Chen & Xiang Meng & Qing Yan, 2024. "Propagating COVID-19 Conspiracy Theories: The Influence of Right-Wing Sources," SAGE Open, , vol. 14(2), pages 21582440241, June.
    20. Yandong Wang & Teng Wang & Xinyue Ye & Jianqi Zhu & Jay Lee, 2015. "Using Social Media for Emergency Response and Urban Sustainability: A Case Study of the 2012 Beijing Rainstorm," Sustainability, MDPI, vol. 8(1), pages 1-17, December.
    21. Adena, Maja & Huck, Steffen, 2024. "Support for a right-wing populist party and subjective well-being: Experimental and survey evidence from Germany," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 19(6), pages 1-16.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:57:y:2023:i:6:d:10.1007_s11135-023-01615-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.