Postmortem memory of public figures in news and social media
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Significance: Who is remembered by society after they die? Although scholars as well as the broader public have speculated about this question since ancient times, we still lack a detailed understanding of the processes at work when a public figure dies and their media image solidifies and is committed to the collective memory. To close this gap, we leverage a comprehensive 5-y dataset of online news and social media posts with millions of documents per day. By tracking mentions of thousands of public figures during the year following their death, we reveal and model the prototypical patterns and biographic correlates of postmortem media attention, as well as systematic differences in how the news vs. social media remember deceased public figures.
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When people of public interest die, this usually leads to a sharp rise in media attention and social media activity that decays in a matter of days and rises again at anniversaries and special dates related to the deceased individual.
“When people of public interest die, this usually leads to a sharp rise in media attention and social media activity that decays in a matter of days (West et al., 2021) and rises again at anniversaries and special dates related to the deceased individual (cf.Ferron & Massa, 2014;Keegan & Brubaker, 2015).”
From Understanding Autobiographical Memory in the Digital Age: The AMEDIA-Model (2024) · cites this paper as West et al., 2021
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Cites
Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market
Salganik, M. J., Dodds, P. S., & Watts, D. J. (2006) · Science · doi:10.1126/science.1121066 · Cited by 2,219 · cited 1× · see citing works
“Given the inherent unpredictability of social systems [34, 47], this would be unlikely to change even if more biographic variables and more data points became available, and if more complex statistical models were to be used.”
Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., Petersen, A. M., Radicchi, F., Sinatra, R., Uzzi, B., et al. (2018) · Science · doi:10.1126/science.aao0185 · Cited by 1,497 · see citing works
Wixted, J. T., & Ebbesen, E. B. (1991) · Psychological Science · doi:10.1111/j.1467-9280.1991.tb00175.x · Cited by 513 · cited 2× · see citing works
“99; details on model fitting in Materials and Methods) significantly better than any of eight alternative models from the literature (46, 50, 51) (details in SI Appendix, Fig.”
The Changing Psychology of Culture From 1800 Through 2000
Greenfield, P. M. (2013) · Psychological Science · doi:10.1177/0956797613479387 · Cited by 391 · see citing works
Flagged first, then by citations
Research works printed but not linked: 41
- [2]H. I. Flower, The Art of Forgetting: Disgrace and Oblivion in Roman Political Culture (University of North Carolina Press, 2006).
- [5]H. L. Roediger III, M. Abel, Collective memory: A new arena of cognitive study. Trends Cogn. Sci. 19, 359– 361 (2015). 25953047
- [6]H. L. Roediger III, K. A. DeSoto, Forgetting the presidents. Science 346, 1106– 1109 (2014). 25430768
- [7]H. L. Roediger III., Competing national memories of World War II. Proc. Natl. Acad. Sci. U.S.A. 116, 16678– 16686 (2019). 31405968 PMC6708356
- [8]G. R. Edgerton, P. C. Rollins, Television Histories: Shaping Collective Memory in the Media Age (University Press of Kentucky, 2001).
- [10]M. Neiger, O. Meyers, E. Zandberg, On Media Memory: Collective Memory in a New Media Age (Springer, 2011).
- [11]B. Zelizer, Covering the Body: The Kennedy Assassination, the Media, and the Shaping of Collective Memory (University of Chicago Press, 1992).
- [13]B. Fowler, The Obituary as Collective Memory (Routledge, 2007).
- [14]J. Hume, Obituaries in American Culture (University Press of Mississippi, 2000).
- [15]N. Starck, Death can make a difference: A comparative study of “quality quartet” obituary practice. Journal. Stud. 9, 911– 924 (2008).
- [16]F. Hanusch, Valuing those close to us: A comparison of German and Australian quality newspapers’ reporting of death in foreign news. Journal. Stud. 9, 341– 356 (2008).
- [17]Cm. Au Yeung, A. Jatowt, “Studying how the past is remembered: Towards computational history through large scale text mining” in Proceedings of the 20th ACM International Conference on Information and Knowledge Management (Association for Computing Machinery, 2011), pp. 1231– 1240.
- [18]T. Huet, J. Biega, F. M. Suchanek, “Mining history with Le Monde” in Proceedings of the 2013 Workshop on Automated Knowledge Base Construction (Association for Computing Machinery, 2013), pp. 49– 54.
- [19]J. Cook, A. Das Sarma, A. Fabrikant, A. Tomkins, “Your two weeks of fame and your grandmother’s” in Proceedings of the 21st International Conference on World Wide Web (Association for Computing Machinery, 2012), pp. 919– 928.
- [21]F. M. Suchanek, N. Preda, Semantic culturomics. Proceedings VLDB Endowment 7, 1215– 1218 (2014).
- [23]K. Z. Gach, C. Fiesler, J. R. Brubaker, “Control your emotions, Potter:” An analysis of grief policing on Facebook in response to celebrity death. Proc. ACM Hum. Comput. Interact. 1, 1– 18 (2017).
- [26]D. Hoe-Lian Goh, C. Sian Lee, An analysis of tweets in response to the death of Michael Jackson. Aslib Proceedings 63, 432– 444 (2011).
- [28]B. C. Keegan, J. R. Brubaker, “‘Is’ to ‘was’: Coordination and commemoration in posthumous activity on Wikipedia biographies” in Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work and Social Computing (Association for Computing Machinery, 2015), pp. 533– 546.
- [29]M. Ferron, P. Massa, “Psychological processes underlying Wikipedia representations of natural and manmade disasters” in Proceedings of the 8th Annual International Symposium on Wikis and Open Collaboration (Association for Computing Machinery, 2012), pp. 1– 10.
- [31]N. Kanhabua, T. N. Nguyen, C. Niederée, “What triggers human remembering of events? A large-scale analysis of catalysts for collective memory in Wikipedia” in Proceedings of the 2014 IEEE/ACM Joint Conference on Digital Libraries (Association for Computing Machinery, 2014), pp. 341– 350.
- [32]R. García-Gavilanes, A. Mollgaard, M. Tsvetkova, T. Yasseri, The memory remains: Understanding collective memory in the digital age. Sci. Adv. 3, e1602368 (2017). 28435881 PMC5381953
- [33]A. Jatowt, D. Kawai, K. Tanaka, “Digital history meets Wikipedia: Analyzing historical persons in Wikipedia” in Proceedings of the 2016 IEEE/ACM Joint Conference on Digital Libraries (Association for Computing Machinery, 2016), pp. 17– 26.
- [34]C. Jara-Figueroa, A. Z. Yu, C. A. Hidalgo, How the medium shapes the message: Printing and the rise of the arts and sciences. PLoS One 14, e0205771 (2019). 30785879 PMC6382096
- [35]J. B. Michel.; Google Books Team, Quantitative analysis of culture using millions of digitized books. Science 331, 176– 182 (2011). 21163965 PMC3279742
- [37]E. A. Pechenick, C. M. Danforth, P. S. Dodds, Characterizing the Google Books corpus: Strong limits to inferences of socio-cultural and linguistic evolution. PLoS One 10, e0137041 (2015). 26445406 PMC4596490
- [38]A. Jatowt, E. Antoine, Y. Kawai, T. Akiyama, “Mapping temporal horizons: Analysis of collective future and past related attention in Twitter” in Proceedings of the 24th International Conference on World Wide Web (Association for Computing Machinery, 2015), pp. 484– 494.
- [39]Y. Sumikawa, A. Jatowt, M. Düring, “Digital history meets microblogging: Analyzing collective memories in Twitter” in Proceedings of the 18th ACM/IEEE Joint Conference on Digital Libraries (Association for Computing Machinery, 2018), pp. 213– 222.
- [41]D. Wang, C. Song, A. L. Barabási, Quantifying long-term scientific impact. Science 342, 127– 132 (2013). 24092745
- [42]S. P. Fraiberger, R. Sinatra, M. Resch, C. Riedl, A. L. Barabási, Quantifying reputation and success in art. Science 362, 825– 829 (2018). 30409804
- [43]R. Sinatra, D. Wang, P. Deville, C. Song, A. L. Barabási, Quantifying the evolution of individual scientific impact. Science 354, aaf5239 (2016). 27811240
- [44]L. Liu., Hot streaks in artistic, cultural, and scientific careers. Nature 559, 396– 399 (2018). 29995850
- [46]C. Candia, C. Jara-Figueroa, C. Rodriguez-Sickert, A. L. Barabási, C. A. Hidalgo, The universal decay of collective memory and attention. Nat. Hum. Behav. 3, 82– 91 (2019). 30932052
- [47]K. Bollacker, C. Evans, P. Paritosh, T. Sturge, J. Taylor, “Freebase: A collaboratively created graph database for structuring human knowledge” in Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data (Association for Computing Machinery, 2008), pp. 1247– 1250.
- [53]S. Ronen., Links that speak: The global language network and its association with global fame. Proc. Natl. Acad. Sci. U.S.A. 111, E5616– E5622 (2014). 25512502 PMC4284551
- [54]T. Martin, J. M. Hofman, A. Sharma, A. Anderson, D. J. Watts, “Exploring limits to prediction in complex social systems” in Proceedings of the 25th International Conference on World Wide Web (Association for Computing Machinery, 2016), pp. 683– 694.
- [56]N. Grinberg, K. Joseph, L. Friedland, B. Swire-Thompson, D. Lazer, Fake news on Twitter during the 2016 U.S. presidential election. Science 363, 374– 378 (2019). 30679368
- [57]A. Bovet, H. A. Makse, Influence of fake news in Twitter during the 2016 US presidential election. Nat. Commun. 10, 7 (2019). 30602729 PMC6315042
- [58]W. X. Zhao., “Comparing Twitter and traditional media using topic models” in Proceedings of the European Conference on Information Retrieval (Association for Computing Machinery, 2011), pp. 338– 349.
- [59]H. Kwak, C. Lee, H. Park, S. Moon, “What is Twitter, a social network or a news media?” in Proceedings of the 19th International Conference on World Wide Web (Association for Computing Machinery, 2010), pp. 591– 600.
- [60]A. Z. Yu, S. Ronen, K. Hu, T. Lu, C. A. Hidalgo, Pantheon 1.0, a manually verified dataset of globally famous biographies. Sci. Data 3, 150075 (2016). 26731133 PMC4700860
- [64]R. West, J. Leskovec, C. Potts, Code and data repository for “Postmortem memory of public figures in news and social media.” GitHub. https://github.com/epfl-dlab/post-mortem-memory. Deposited 28 May 2021. PMC8463883 34526401
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Understanding Autobiographical Memory in the Digital Age: The AMEDIA-Model
Hutmacher, F., Appel, M., & Schwan, S. (2024) · Psychological Inquiry · doi:10.1080/1047840x.2024.2384125 · Cited by 12 · see citing works
- Authors
- West, R., Leskovec, J., & Potts, C.
- Affiliations
- École Polytechnique Fédérale de Lausanne (CH)
- Stanford University (US)
- Corresponding author
- West, Robert
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2021-09-15
- Volume
- 118
- Issue
- 38
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC8463883
- OpenAlex
- W3157875203
- Cited by
- 15
- References
- 4
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 3 · 2023: 5 · 2022: 2
- FWCI
- 2.27
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- arXiv (Cornell University)
- Funders
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (200021_185043)
- National Science Foundation (OAC-1835598, OAC-1934578, CCF-1918940, IIS-2030477)
- École Polytechnique Fédérale de Lausanne (CROSS 2019)
- Topics
- Social Sciences › Psychology › Social Psychology › Memory, Trauma, and Commemoration
- Social Sciences › Anthropology › Death, Funerary Practices, and Mourning
- Social Sciences › Arts and Humanities › Philosophy › Memory, History, Trauma, Identity
- Keywords
- collective memory, public figures, media attention, Twitter, news media, cultural memory, communicative memory, unnatural death, age at death, political leaders, artists
- MeSH terms
- Mass Gatherings, Communication, Humans, Mass Media, Memory, Social Identification, Social Media, Sociological Factors
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