Abstract
In online media environments, nostalgia can be used as important ingredient of propaganda strategies, specifically, by creating societal pessimism. This work addresses the automated detection of nostalgic text as a first step towards automatically identifying nostalgia-based manipulation strategies. We compare the performance of standard machine learning approaches on this challenge and demonstrate the successful transfer of the best performing approach to real-world nostalgia detection in a case study.
Original language | English |
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Title of host publication | Disinformation in open online media |
Subtitle of host publication | First Multidisciplinary International Symposium, MISDOOM 2019, Hamburg, Germany, February 27 – March 1, 2019, Revised Selected Papers |
Editors | Christian Grimme, Mike Preuß, Frank Takes, Annie Waldherr |
Publisher | Springer |
Pages | 48-58 |
Number of pages | 11 |
DOIs | |
Publication status | Published - 2020 |
Externally published | Yes |
Event | Multidisciplinary International Symposium on Disinformation in Open Online Media, MISDOOM 2019 - Hamburg, Germany Duration: 27 Feb 2019 → 1 Mar 2019 https://2019.misdoom.org/ |
Publication series
Name | Lecture Notes in Computer Science |
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Volume | 12021 |
Conference
Conference | Multidisciplinary International Symposium on Disinformation in Open Online Media, MISDOOM 2019 |
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Abbreviated title | MISDOOM 2019 |
Country/Territory | Germany |
City | Hamburg |
Period | 27/02/19 → 1/03/19 |
Internet address |