Promoting and countering misinformation during Australia's 2019-2020 bushfires
A Case Study of Polarisation
Bibliographic Data
| ID | 4616735 |
|---|---|
| Authors | Doreen Weber (0000-0003-3830-9014, Defence Science and Technology Group, corresponding author), Lucia Falzon (0000-0003-3134-4351, The University of Melbourne), Lewis Mitchell (0000-0001-8191-1997, ARC Centre of Excellence for Mathematical and Statistical Frontiers), Mehwish Nasim (0000-0003-0683-9125, Flinders University) |
| Year | 2022 |
| Volume | 12 |
| Issue | 1 |
| Pages | 64-64 |
| Publication date | 2022-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-022-00892-x |
| PMID | 35789892 |
| OpenAlex | W4221159398 |
| Language | EN |
| Citations received | 5 |
| References cited | 62 |
During Australia's unprecedented bushfires in 2019-2020, misinformation blaming arson surfaced on Twitter using . The extent to which bots and trolls were responsible for disseminating and amplifying this misinformation has received media scrutiny and academic research. Here, we study Twitter communities spreading this misinformation during the newsworthy event, and investigate the role of online communities using a natural experiment approach-before and after reporting of bots promoting the hashtag was broadcast by the mainstream media. Few bots were found, but the most bot-like accounts weresocial bots, which present as genuine humans, and trolling behaviour was evident. Further, we distilled meaningful quantitative differences between two polarised communities in the Twitter discussion, resulting in the following insights. First,Supportersof the arson narrative promoted misinformation by engaging others directly with replies and mentions using hashtags and links to external sources. In response,Opposersretweeted fact-based articles and official information. Second, Supporters were embedded throughout their interaction networks, but Opposers obtained high centrality more efficiently despite their peripheral positions. By the last phase, Opposers and unaffiliated accounts appeared to coordinate, potentially reaching a broader audience. Finally, the introduction of the bot report changed the discussion dynamic: Opposers only responded immediately, while Supporters countered strongly for days, but new unaffiliated accounts drawn into the discussion shifted the dominant narrative from arson misinformation to factual and official information. This foiled Supporters' efforts, highlighting the value of exposing misinformation. We speculate that the communication strategies observed here could inform counter-strategies in other misinformation-related discussions
Internet privacy · Mainstream · Media studies · Misinformation · Narrative · Political science · Population · Scrutiny · Social media · Sociology · Computer Science · Law · Misinformation and Its Impacts · Public Relations and Crisis Communication · Social Media and Politics
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| Unique citing works | 5 |
|---|---|
| Citations per year | 1,67 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 5 |