Of Pins and Tweets: Investigating How Users Behave Across Image- and Text-Based Social Networks
Open accessAbstract
Today, it is the norm for online social (OSN) users to have accounts on multiple services. For example, a recent study showed that 34% of all Twitter users also use Pinterest. This situation leads to interesting questions such as: Are the activities that users perform on each site disjoint? Alternatively, if users perform the same actions on multiple sites, where does the information originate? Given the interlinking between social networks, failure to understand activity across multiple sites may obfuscate the true information dissemination dynamics of the social web. In this study, we take the first steps towards a more complete understanding of user behavior across multiple OSNs. We collect a sample of over 30,000 users that have accounts on both Twitter and Pinterest, crawling their profile information and activity on a daily basis for a period of almost three months. We develop a novel methodology for comparing activity across these two sites. We find that the global patterns of use across the two sites differ significantly, and that users tend to post items to Pinterest before posting them on Twitter. Our findings can inform the understanding of the behavior of users on individual sites, as well as the dynamics of sharing across the social web.
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Studies looking at similarities and differences among social platforms found differences with respect to user personalities, news spreading, or content sharing.
“For instance, studies looking at similarities and differences among social platforms found differences with respect to user personalities (Hughes et al., 2012), news spreading (Lerman and Ghosh, 2010), or content sharing (Ottoni et al., 2014).”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Ottoni et al., 2014
Cites
The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods
Tausczik, Y. R., & Pennebaker, J. W. (2010) · Journal of Language and Social Psychology · doi:10.1177/0261927x09351676 · Cited by 5,774 · see citing works
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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 · see citing works
“9 For instance, studies looking at similarities and differences among social platforms found differences with respect to user personalities (Hughes et al., 2012), news spreading (Lerman and Ghosh, 2010), or content sharing (Ottoni et al., 2014).”
BackgroundSocial Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Olteanu, A., Castillo, C., Diaz, F., & Kiciman, E. (2016) · doi:10.2139/ssrn.2886526 · Cited by 763 · see citing works
- Authors
- Ottoni, R., Las Casas, D., Pesce, J. P., Meira Jr., W., Wilson, C., Mislove, A., & Almeida, V.
- Affiliations
- Universidade Federal de Minas Gerais (BR)
- Northeastern University (US)
- Venue
- Proceedings of the International AAAI Conference on Web and Social Media
- Published
- 2014-05-16
- Volume
- 8
- Issue
- 1
- Pages
- 386-395
- ISSN
- 2162-3449 (ISSN-L)
- 2334-0770
- OpenAlex
- W2183238970
- Cited by
- 75
- References
- 1
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3 · 2022: 2 · 2021: 3 · 2020: 4 · 2019: 5 · 2018: 10 · 2017: 11 · 2016: 13 · 2015: 15 · 2014: 6 · 2013: 1
- FWCI
- 13.81
- Type
- conference paper
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Proceedings of the International AAAI Conference on Web and Social Media (publishedVersion)
- AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) (submittedVersion)
- Funders
- National Science Foundation (1054233, 1319019)
- Amazon Web Services
- Army Research Office (W911NF-12-1-0556, W911NF)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Computer Science › Computer Networks and Communications › Media and Digital Communication
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Keywords
- Twitter, Pinterest, information dissemination, user activity patterns, Web 2.0
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