Cited by 133Computational and Text Analysis MethodsMedia and Digital CommunicationDigital Humanities and Scholarship

The DOI matches its Crossref record; 74 of the 75 references it cites were found in a registry or an index.

On the Interpretation of Digital Trace Data in Communication and Social Computing Research

Freelon, Deen·2014·Journal of Broadcasting & Electronic Media

DOI 10.1080/08838151.2013.875018

Open this paper in CoChat — free account

Abstract

The widespread availability of analytical tools for Big Data offers enormous opportunities and challenges for communication researchers. In contrast to user-generated texts, digital trace data (evidence of online user activities such as hyperlinks and retweets) represent a new methodological frontier for the field. However, interpretive strategies remain scattered and ad hoc with few best practices to guide them. To help remedy this situation, this article reviews recent scholarship in both communication and social computing research that has incorporated three common types of trace data: hyperlinks, Twitter followers, and retweets. It finds that while researchers in both fields have interpreted each trace in a variety of ways, they have largely declined to explain the validity of their interpretations.

Integrity signals

Registry

Crossref · 10.1080/08838151.2013.875018

Cites

74 of 74 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Social network sites: definition, history, and scholarship
boyd, D. M., & Ellison, N. B. (2007) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2007.00393.x · Cited by 16,251
Untitled work
(1999) · Cited by 12,854
What is Twitter, a social network or a news media?
Kwak, H., Lee, C., Park, H., & Moon, S. (2010) · Proceedings of the 19th international conference on World wide web · doi:10.1145/1772690.1772751 · Cited by 6,652
Untitled work
(2011) · Cited by 5,203
I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience
Marwick, A. E., & boyd, D. (2011) · New Media & Society · doi:10.1177/1461444810365313 · Cited by 4,612
Why we twitter
Java, A., Song, X., Finin, T., & Tseng, B. L. (2007) · doi:10.1145/1348549.1348556 · Cited by 2,662
Information credibility on twitter
Castillo, C., Mendoza, M., & Poblete, B. (2011) · Proceedings of the 20th international conference on World wide web · doi:10.1145/1963405.1963500 · Cited by 2,593
Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter
Boyd, D., Golder, S., & Lotan, G. (2010) · 2010 43rd Hawaii International Conference on System Sciences · doi:10.1109/hicss.2010.412 · Cited by 2,051
Journal of Computer-Mediated Communication
(2018) · Journal of Computer-Mediated Communication · doi:10.1111/(issn)1083-6101 · Cited by 1,894
TwitterRank
Weng, J., Lim, E., Jiang, J., & He, Q. (2010) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/1718487.1718520 · Cited by 1,780

Show all 75 references

Research works printed but not linked: 6

Coddington M., 2012, International Journal of Communication, 6, 2007
10.1111/j.1460-2466.2005.tb02682.x · DOI
Manyika J., 2011, McKinsey Global Institute, 1
Moe H., 2012, International Journal of Communication, 6, 1222
Papacharissi Z., 2012, International Journal of Communication, 6, 1989
Wilson C., 2011, International Journal of Communication, 5

Sorted by citations

The Pushshift Reddit Dataset
Baumgartner, J., Zannettou, S., Keegan, B., Squire, M., & Blackburn, J. (2020) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v14i1.7347 · Cited by 881
Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Olteanu, A., Castillo, C., Diaz, F., & Kıcıman, E. (2019) · Frontiers in Big Data · doi:10.3389/fdata.2019.00013 · Cited by 763
“Norms are also sensitive to context, as the meaning of the same action or mechanism may change under diﬀerent circumstances (Freelon, 2014).”
Background
Big questions for social media big data: Representativeness, validity and other methodological pitfalls
Tufekci, Z. (2014) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v8i1.14517 · Cited by 780
Quantifying the power and consequences of social media protest
Freelon, D., McIlwain, C. D., & Clark, M. D. (2016) · New Media & Society · doi:10.1177/1461444816676646 · Cited by 392
Self-citation
Taking Stock of the Toolkit
Boumans, J. W., & Trilling, D. (2015) · Digital Journalism · doi:10.1080/21670811.2015.1096598 · Cited by 248
Building a complementary agenda for business process management and digital innovation
Mendling, J., Pentland, B. T., & Recker, J. (2020) · European Journal of Information Systems · doi:10.1080/0960085x.2020.1755207 · Cited by 185
Digital Trace Data Collection for Social Media Effects Research: APIs, Data Donation, and (Screen) Tracking
Ohme, J., Araujo, T., Boeschoten, L., Freelon, D., Ram, N., Reeves, B. B., & Robinson, T. N. (2024) · Communication Methods and Measures · doi:10.1080/19312458.2023.2181319 · Cited by 208
Self-citation
Tracking the release of IPCC AR5 on Twitter: Users, comments, and sources following the release of the Working Group I Summary for Policymakers
Newman, T. P. (2017) · Public Understanding of Science · doi:10.1177/0963662516628477 · Cited by 124
Reinforcing attitudes in a gatewatching news era: Individual-level antecedents to sharing fact-checks on social media
Amazeen, M. A., Vargo, C. J., & Hopp, T. (2018) · Communication Monographs · doi:10.1080/03637751.2018.1521984 · Cited by 126
Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Olteanu, A., Castillo, C., Diaz, F., & Kiciman, E. (2016) · doi:10.2139/ssrn.2886526 · Cited by 763
Computational Social Science and the Study of Political Communication
Theocharis, Y., & Jungherr, A. M. (2020) · Political Communication · doi:10.1080/10584609.2020.1833121 · Cited by 106
The Relationship Between Cyberbalkanization and Opinion Polarization: Time-Series Analysis on Facebook Pages and Opinion Polls During the Hong Kong Occupy Movement and the Associated Debate on Political Reform
Chan, C., & Fu, K. (2017) · Journal of Computer-Mediated Communication · doi:10.1111/jcc4.12192 · Cited by 89
Interactive Behavior in Political Discussions on Twitter: Politicians, Media, and Citizens’ Patterns of Interaction in the 2015 and 2016 Electoral Campaigns in Spain
Guerrero-Solé, F. (2018) · Social Media + Society · doi:10.1177/2056305118808776 · Cited by 75
Self-Reported Versus Digitally Recorded: Measuring Political Activity on Facebook
Haenschen, K. (2019) · Social Science Computer Review · doi:10.1177/0894439318813586 · Cited by 75
Scaling up Content Analysis
Trilling, D., & Jonkman, J. G. F. (2018) · Communication Methods and Measures · doi:10.1080/19312458.2018.1447655 · Cited by 64
Bringing Context Inside Process Research with Digital Trace Data
Pentland, B. T., Recker, J., Wolf, J. R., & Wyner, G. M. (2020) · Journal of the Association for Information Systems · doi:10.17705/1jais.00635 · Cited by 60
Emerging communication technology research: Theoretical and methodological variables in the last 16 years and future directions
Borah, P. (2015) · New Media & Society · doi:10.1177/1461444815621512 · Cited by 45
Detecting Pain Points from User-Generated Social Media Posts Using Machine Learning
Salminen, J. O., Mustak, M., Corporan, J., Jung, S., & Jansen, B. J. J. (2022) · Journal of Interactive Marketing · doi:10.1177/10949968221095556 · Cited by 50
Community Detection in Political Discussions on Twitter
Guerrero-Solé, F. (2015) · Social Science Computer Review · doi:10.1177/0894439315617254 · Cited by 49
‘How could anyone have predicted that #AskJameis would go horribly wrong?’ public relations, social media, and hashtag hijacking
Sanderson, J., Barnes, K., Williamson, C., & Kian, E. M. (2015) · Public Relations Review · doi:10.1016/j.pubrev.2015.11.005 · Cited by 51
The Digital Phenotype: a Philosophical and Ethical Exploration
Loi, M. (2018) · Philosophy & Technology · doi:10.1007/s13347-018-0319-1 · Cited by 44
Search Engine Use for Health-Related Purposes: Behavioral Data on Online Health Information-Seeking in Germany
Bachl, M., Link, E., Mangold, F., & Stier, S. (2024) · Health Communication · doi:10.1080/10410236.2024.2309810 · Cited by 39
Social computing in currency exchange
Chamoso, P., González‐Briones, A., Rivas, A., la Prieta, F. D., & Corchado, J. M. (2019) · Knowledge and Information Systems · doi:10.1007/s10115-018-1289-4 · Cited by 38
A Big Data Approach to Assessing the Impact of Social Norms: Reporting One’s Exercise to a Social Media Audience
Carpenter, C. J., & Amaravadi, C. S. (2016) · Communication Research · doi:10.1177/0093650216657776 · Cited by 38
From Silence to #WhyIStayed: Locating Our Stories and Finding Our Voices
Weathers, M., Sanderson, J., Neal, A., & Gramlich, K. (2016) · Qualitative Research Reports in Communication · doi:10.1080/17459435.2016.1143385 · Cited by 39
The crossroads of digital phenotyping
Davidson, B. I. (2020) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2020.11.009 · Cited by 37
New Guidelines for Null Hypothesis Significance Testing in Hypothetico-Deductive IS Research
Mertens, W., & Recker, J. (2023) · Technology, work and globalization · doi:10.1007/978-3-031-38719-7_13 · Cited by 33
Process science: the interdisciplinary study of socio-technical change
Brocke, J. V., van der Aalst, W. M. P., Berente, N., van Dongen, B. F., Grisold, T., Kremser, W., Mendling, J., Pentland, B. T., Roeglinger, M., Rosemann, M., et al. (2024) · Process Science · doi:10.1007/s44311-024-00001-5 · Cited by 33
Conceptualizing the dialogical structure of mass communication: A comparison of the dialogical networks and mediated social communication approaches
Baumgartner, A., Fürst, S., & Schönhagen, P. (2021) · Discourse Context & Media · doi:10.1016/j.dcm.2021.100546 · Cited by 29
Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a Dutch cultural controversy on Twitter
Keuchenius, A., Törnberg, P., & Uitermark, J. (2021) · PLOS ONE · doi:10.1371/journal.pone.0256696 · Cited by 27
Generating impactful situated explanations through digital trace data
Grisold, T., Kremser, W., Mendling, J., Recker, J., Brocke, J. V., & Wurm, B. (2023) · Journal of Information Technology · doi:10.1177/02683962231208724 · Cited by 36
Collective Trolling as a Form of Organizational Resistance: Analysis of the #Justiceforbradswife Twitter Campaign
Kirkwood, G. L., Payne, H. J., & Mazer, J. P. (2019) · Communication Studies · doi:10.1080/10510974.2019.1610015 · Cited by 24
Trace interviews: An actor-centered approach
Dubois, E., & Ford, H. (2015) · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · Cited by 24
On the Pivotal Role of Data in Sustainability Transformations
Püchel, L., Wang, C., Buhmann, K., Brandt, T., Schweinitz, F. S. V., Edinger‐Schons, L. M., Brocke, J. V., Legner, C., Teracino, E. A., & Mardahl, T. D. (2024) · Business & Information Systems Engineering · doi:10.1007/s12599-024-00904-4 · Cited by 34
Why the Data Revolution Needs Qualitative Thinking
Tanweer, A., Gade, E. K., Krafft, P. M., & Dreier, S. K. (2021) · Harvard Data Science Review · doi:10.1162/99608f92.eee0b0da · Cited by 22
Liking, Tweeting and Posting: An Analysis of Community Engagement through Social Media Platforms
Steinmetz, C., Rahmat, H., Marshall, N., Bishop, K., Thompson, S. M., Park, M., Corkery, L., & Tietz, C. (2020) · Urban Policy and Research · doi:10.1080/08111146.2020.1792283 · Cited by 21
The use of emotions in conspiracy and debunking videos to engage publics on YouTube
Kim, S. J., & Chen, K. (2022) · New Media & Society · doi:10.1177/14614448221105877 · Cited by 30
‘Datafying’ Broadcasting: Exploring the Role of Big Data and Its Implications for Competing in a Big Data-Driven TV Ecosystem
Murschetz, P. C., & Prandner, D. (2018) · Contributions to management science · doi:10.1007/978-3-319-71722-7_4 · Cited by 21
Fifty years of agenda-setting research
Vargo, C. J. (2018) · The Agenda Setting Journal · doi:10.1075/asj.18023.var · Cited by 20
“Rough Week for Testosterone”: Public Commentary around the Ivy League’s Decision to Restrict Tackle Football in Practice
Cranmer, G. A., & Sanderson, J. (2018) · Western Journal of Communication · doi:10.1080/10570314.2018.1441431 · Cited by 20
A Tutorial for Using Twitter Data in the Social Sciences: Data Collection, Preparation, and AnalysisPreprint
JJrgens, P., & Jungherr, A. M. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2710146 · Cited by 18
Digital Diaspora Activism at the Margins: Unfolding Rohingya Diaspora Interactions on Facebook (2017–2022)
Ansar, A., & Maitra, J. (2024) · Social Media + Society · doi:10.1177/20563051241228603 · Cited by 18
Worlds of Agents: Prospects of Agent-Based Modeling for Communication Research
Waldherr, A., Hilbert, M., & González‐Bailón, S. (2021) · Communication Methods and Measures · doi:10.1080/19312458.2021.1986478 · Cited by 20
The Morality Machine: Tracking Moral Values in Tweets
Teernstra, L., van der Putten, P., Noordegraaf‐Eelens, L., & Verbeek, F. J. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46349-0_3 · Cited by 18
Conceptualisation of Digital Traces for the Identification of Informal Networks in Enterprise Social Networks
Behrendt, S., Richter, A., & Riemer, K. (2014) · Tuwhera (Auckland University of Technology) · Cited by 15
Kulturen im Wandel: Zur nonlinearen Brüchigkeit von Mediatisierungsprozessen
Grenz, T., & Pfadenhauer, M. (2017) · Springer eBooks · doi:10.1007/978-3-658-16084-5_9 · Cited by 17
#NotOkay: Stories of sexual assault in the midst of the 2016 U.S. presidential election
Jenkins, A., & Mazer, J. P. (2017) · Qualitative Research Reports in Communication · doi:10.1080/17459435.2017.1404487 · Cited by 19
Supporting digital discourse? The deliberative function of links on Twitter
Jakob, J. (2020) · New Media & Society · doi:10.1177/1461444820972388 · Cited by 16
Managing to release early, often and on time in the OpenStack software ecosystem
Teixeira, J. A., & Karsten, H. (2019) · Journal of Internet Services and Applications · doi:10.1186/s13174-019-0105-z · Cited by 17
Adrian Peterson and the “Wussification of America”: Football and Myths of Masculinity
Foote, J. G., Butterworth, M. L., & Sanderson, J. (2016) · Communication Quarterly · doi:10.1080/01463373.2016.1227347 · Cited by 15
Sosyal Bilimlerde Büyük Veri Analitiği, Yapay Zeka ve Makine Öğreniminin Kullanımı
Mevlüt Hürol, M. E. T. E. (2023) · Anadolu Üniversitesi Sosyal Bilimler Dergisi · doi:10.18037/ausbd.1272565 · Cited by 16
Understanding electronic word of behavior: conceptualization of the observable digital traces of consumers’ behaviors
Kunst, K., & Vatrapu, R. (2018) · Electronic Markets · doi:10.1007/s12525-018-0301-x · Cited by 11
Beyond popularity: A user perspective on observable behaviours in a digital platform
Kunst, K., Ringberg, T., & Vatrapu, R. (2021) · Information Systems Journal · doi:10.1111/isj.12365 · Cited by 11
Online networking behaviour of tourism stakeholders in a multi-destination region: A hyperlink network analysis
Herasimovich, V., Alzua-Sorzabal, A., & Guereño-Omil, B. (2023) · Journal of Destination Marketing & Management · doi:10.1016/j.jdmm.2023.100844 · Cited by 11
What Framework Promotes Saliency of Climate Change Issues on Online Public Agenda: A Quantitative Study of Online Knowledge Community Quora
Shi, W., Chen, C., Xiong, J., & Fu, H. (2019) · Sustainability · doi:10.3390/su11061619 · Cited by 11
Computational communication research
Matei, S. A., & Kee, K. F. (2019) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1304 · Cited by 10
Blogs e redes sociais na atenção à saúde da família: o que a comunicação online traz de novo?
Barcelos, P., Lima, T. V., & de Aguiar, A. C. (2020) · Reciis · doi:10.29397/reciis.v14i1.1747 · Cited by 9
Not So Distinct After All: Assessing Social Stratification of News Users on the Web
Ørmen, J. (2018) · Journalism Studies · doi:10.1080/1461670x.2018.1539342 · Cited by 9
Big Data y televisión. Una reflexión crítica sobre el auge del Big Data como nuevo paradigma tecno-económico, y su impacto en el concepto de target de audiencia
Murschetz, P. C., & Schlütz, D. (2018) · Fonseca Journal of Communication · doi:10.14201/fjc2018172338 · Cited by 8
Impact of Sparse and Dense Deployment of Nodes Under Different Propagation Models in Manets
Hussain, A., Hussain, T., Ali, I., & Khan, M. R. (2020) · ADCAIJ ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL · doi:10.14201/adcaij2020916184 · Cited by 8
Beyond the Wall: Mapping Twitter in ChinaPreprint
Song, S., Faris, R., & Kelly, J. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2685358 · Cited by 8
Who Sets Social Media Sentiment?: Sentiment Contagion in the 2016 U.S. Presidential Election Media Tweet Network
Joa, C. Y., & Yun, G. W. (2020) · Journalism Practice · doi:10.1080/17512786.2020.1856708 · Cited by 7
Making sense of Starbucks’ anti-bias training and the arrests of two African American men: A thematic analysis of Whites’ Facebook and Twitter comments
Karlsen, A. S., & Scott, K. D. (2019) · Discourse Context & Media · doi:10.1016/j.dcm.2019.100332 · Cited by 13
Untapped Potential: Designed Digital Trace Data in Online Survey Experiments
Macke, E., Daviss, C., & Williams-Baron, E. (2024) · Sociological Methods & Research · doi:10.1177/00491241241268770 · Cited by 7
The IT Artifact in People Analytics: Reviewing Tools to Understand a Nascent Field
Hüllmann, J. A., Krebber, S., & Troglauer, P. (2021) · Lecture notes in information systems and organisation · doi:10.1007/978-3-030-86800-0_18 · Cited by 7
Comparative Process-oriented Research Using Social Media and Historical Text
Murthy, D. (2017) · Sociological Research Online · doi:10.1177/1360780417731272 · Cited by 6
Quantitative intersectional data (QUINTA): a #metoo case study
Boyd, A. E. (2021) · Digital Commons-DePaul (DePaul University) · Cited by 6
Narrative Networks in Routine Dynamics
Pentland, B. T., & Kim, I. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108993340.016 · Cited by 6
Unraveling China’s digital traces: evaluating communication scholarship through a sociotechnical lens
Chen, K., Lu, Y., & Wang, Y. (2023) · Chinese Journal of Communication · doi:10.1080/17544750.2023.2264406 · Cited by 5
An exploratory study of information re-finding behaviour modes of Chinese college students on social media: video diary analysis from Chinese platforms
Ma, X., & Fan, X. (2024) · Behaviour and Information Technology · doi:10.1080/0144929x.2024.2331261 · Cited by 5
Tendencies and characteristics of public fitness behavior in the digital era: an Internet ethnography study based on the K Community in China
Chen, J., & Ye, S. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1414837 · Cited by 5
Levels of Trace Data for Social and Behavioural Science Research
Crowston, K. (2017) · Computational social sciences · doi:10.1007/978-3-319-59186-5_4 · Cited by 5
Expression and Reception: An Analytic Method for Assessing Message Production and Consumption in CMC
Namkoong, K., Shah, D. V., McLaughlin, B., Chih, M., Moon, T. J., Hull, S. J., & Gustafson, D. H. (2017) · Communication Methods and Measures · doi:10.1080/19312458.2017.1313396 · Cited by 8
The Knowledge-Remixing Bottleneck
Groth, P. (2013) · IEEE Intelligent Systems · doi:10.1109/mis.2013.138 · Cited by 4
Collecting data from Internet (and other platform) users for mental health research
Lahoud, A. A., Gladstone, T. R., Clark, S. B., & Flessner, C. A. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-822201-0.00015-0 · Cited by 4
Somut Olmayan Kültürel Mirasın korunmasında yapay zekâ, veri bilimi ve makine öğrenmesinden yararlanma
Nejla, O. R. T. A. (2024) · RumeliDE Dil ve Edebiyat Araştırmaları Dergisi :/RumeliDe Dil ve Edebiyat Araştırmaları Dergisi · doi:10.29000/rumelide.1439731 · Cited by 8
Verstrickt in der Rhetorik der Technologie-, Daten- und Medienunternehmen? Zu Problematiken im Umgang mit nicht-wissenschaftlichen Nutzungsdaten
Fürst, S. (2021) · Studies in Communication and Media · doi:10.5771/2192-4007-2021-2-175 · Cited by 4
How consistent are smartphone application preferences? A descriptive study of mobile application repertoires using behavioral dataPreprint
Parry, D. A., & Sewall, C. J. R. (2021) · doi:10.31235/osf.io/jzxun · Cited by 4
Search Engine Use for Health-Related Purposes: Behavioral Data on Online Health Information-Seeking in GermanyPreprint
Bachl, M., Link, E., Mangold, F., & Stier, S. (2023) · doi:10.31219/osf.io/bxp5j · Cited by 4
Digital politics in transition and the new logics of fluid visibility on social media: The Ocasio-Cortez case
Battista, D., & Cervi, L. (2025) · Society Register · doi:10.14746/sr.2025.9.4.02 · Cited by 3
Research Methods
Recker, J. (2021) · Progress in IS · doi:10.1007/978-3-030-85436-2_5 · Cited by 4
Big Data-Analysen und qualitative Forschungsmethodik
Mahrt, M. (2016) · Springer eBooks · doi:10.1007/978-3-658-08460-8_56-1 · Cited by 2
A Systems Approach to Studying Online Communities
Foote, J. (2022) · Media and Communication · doi:10.17645/mac.v10i2.5042 · Cited by 6
Big Data-Analysen und qualitative Forschungsmethodik
Mahrt, M. (2020) · Springer eBooks · doi:10.1007/978-3-658-08357-1_56 · Cited by 3
Inferring Individual-Level Characteristics from Digital Trace Data
Freelon, D. (2018) · Routledge eBooks · doi:10.4324/9781351209434-6 · Cited by 3
Self-citation
Processual Shadows
Pentland, B. T., Wolf, J. R., Xie, Y., Kim, I., Frank, K. A., & Pentland, A. P. (2024) · doi:10.1093/oso/9780198899457.003.0007 · Cited by 2
Sosyal Medyada Güç İstenci Savunma Mekanizmaları İle Veri İlişkisini Dijital Yerliler Üzerinden İncelemek
Tan, H., & ŞENKAL, Y. (2024) · Uluslararası İnsan Çalışmaları Dergisi · doi:10.35235/uicd.1506598 · Cited by 2
Who Will Help You to Practice Good Health Habits and Who Will Give You Eating Disorders? Analysis of WeightWatchers Twitter Network
Park, S., Joa, C. Y., & Labbe, B. R. (2022) · Health & New Media Research · doi:10.22720/hnmr.2022.6.1.035 · Cited by 2
Digital innovation management : investigating digital trace data in online communities
Mankevich, V. N. (2019) · DiVA at Umeå University (Umeå University) · Cited by 2
Others are more affected than me: the influence of presumed influence and affective responses on misinformation correction intentions
Ho, S. S., Jin, J., Ou, M., & Huang, N. M. (2026) · Online Information Review · doi:10.1108/oir-03-2025-0183 · Cited by 1
An open-source platform for multimodal digital trace data collection from smartphones
Kim, I., Boffa, J., Cho, M.-J., Conroy, D. E., Kline, N., Haber, N., Robinson, T. N., Reeves, B. B., & Ram, N. (2026) · Nature Health · doi:10.1038/s44360-026-00072-7 · Cited by 1
Designing Process Mining to Mitigate Electronic Performance Monitoring Risks
Nacke, J., Plattfaut, R., & Riedl‬, R. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-28570-6_12 · Cited by 1
Is it ‘Fake News’? Intelligence Community expertise and news dissemination as measurements for media reliability
Rendon, H., Wilson, A. G., & Stegall, J. (2018) · Intelligence & National Security · doi:10.1080/02684527.2018.1507381 · Cited by 1
Social media network homophily among political candidates in multilevel settings
Coffé, H., Cioroianu, I., & Vandenberghe, M. (2022) · Regional & Federal Studies · doi:10.1080/13597566.2022.2107632 · Cited by 2
Using browser data to understand desires to spend time online.
McCrosky, J. D., Parry, D. A., Sewall, C. J. R., & Orben, A. C. (2023) · Technology Mind and Behavior · doi:10.1037/tmb0000095 · Cited by 1
Media as cookie cutters
Pfurtscheller, D. (2024) · Pragmatics & beyond. New series · doi:10.1075/pbns.348.06pfu · Cited by 1
The Citizen in Electoral Discourse: A Preliminary Study
Paskarina, C., Hermawati, R., & Nuraeni, N. (2019) · International Symposium on Indonesian Politics (SIP) · doi:10.4108/eai.25-6-2019.2287970 · Cited by 1
Sociale mediers rolle i politisk kommunikation: et litteraturstudie
Schwartz, S. A. (2019) · Politik · doi:10.7146/politik.v22i2.117707 · Cited by 1
Race for attention: Twitter campaign of Italian party leaders before the 2018 parliamentary elections
Takács, L. (2022) · Conjuntura Internacional · doi:10.5752/p.1809-6182.2021v18n2p26-35 · Cited by 1
UNDERSTANDING THE SCHOLARLY COMMUNICATION PROCESS THROUGH DIGITAL TRACES: A STUDY OF TWITTER
Xu, S. (2020) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/f65m-3m60 · Cited by 1

Authors: Freelon, D.
Affiliations: American University (US)
Corresponding author: Freelon, Deen
ORCID: Freelon, Deen
Venue: Journal of Broadcasting & Electronic Media
Publisher: Informa UK Limited
Published: 2014-01-02
Volume: 58
Issue: 1
Pages: 59-75
ISSN: 0883-8151 (ISSN-L)
1550-6878
DOI: 10.1080/08838151.2013.875018
OpenAlex: W2074336863
Cited by: 132
References: 75
Citations by year: 2026: 15 · 2025: 5 · 2024: 13 · 2023: 10 · 2022: 8 · 2021: 15 · 2020: 14 · 2019: 12 · 2018: 14 · 2017: 6 · 2016: 8 · 2015: 9 · 2014: 2
FWCI: 52.16
Type: journal article
Language: en
Open access: closed
Locations: Journal of Broadcasting & Electronic Media (publishedVersion)
Topics: Social Sciences › General Social Sciences › Computational and Text Analysis Methods
Social Sciences › Communication › Media and Digital Communication
Social Sciences › Arts and Humanities › Literature and Literary Theory › Digital Humanities and Scholarship
Keywords: digital traces, interpretive strategies, hyperlinks, Twitter followers, retweets, social computing, communication research methods, big data, validity of interpretation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

On the Interpretation of Digital Trace Data in Communication and Social Computing Research

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks