Online Abuse toward Candidates during the UK General Election 2019: Working Paper

• URL: http://arxiv.org/abs/2001.08686v2
• Date: Thu, 30 Jan 2020 17:33:21 GMT
• Title: Online Abuse toward Candidates during the UK General Election 2019: Working Paper
• Authors: Genevieve Gorrell, Mehmet E Bakir, Ian Roberts, Mark A Greenwood, Kalina Bontcheva
• Abstract summary: We collected 4.2 million tweets sent to or from election candidates in the six week period spanning from the start of November until shortly after the December 12th election. We found abuse in 4.46% of replies received by candidates, up from 3.27% in the matching period for the 2017 UK general election. On average, men received more general and political abuse; women received more sexist abuse.
• Score: 0.9741305928417096
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: The 2019 UK general election took place against a background of rising online hostility levels toward politicians and concerns about its impact on democracy. We collected 4.2 million tweets sent to or from election candidates in the six week period spanning from the start of November until shortly after the December 12th election. We found abuse in 4.46\% of replies received by candidates, up from 3.27\% in the matching period for the 2017 UK general election. Abuse levels have also been climbing month on month throughout 2019. Abuse also escalated throughout the campaign period. Abuse focused mainly on a small number of high profile politicians. Abuse is "spiky", triggered by external events such as debates, or certain tweets. Abuse increases when politicians discuss inflammatory topics such as borders and immigration. There may also be a backlash on topics such as social justice. Some tweets may become viral targets for personal abuse. On average, men received more general and political abuse; women received more sexist abuse. MPs choosing not to stand again had received more abuse during 2019.

Related papers

• On the Use of Proxies in Political Ad Targeting [49.61009579554272]
  We show that major political advertisers circumvented mitigations by targeting proxy attributes. Our findings have crucial implications for the ongoing discussion on the regulation of political advertising.
  arXiv  Detail & Related papers  (2024-10-18T17:15:13Z)
• Finding Hidden Swing Voters in the 2022 Italian Elections Twitter Discourse [1.3654846342364308]
  We examine the dynamics of political messaging and voter behavior on Twitter during the 2022 Italian general elections. Our analysis reveals that during election periods, the popularity of politicians increases, and there is a notable variation in the use of persuasive language techniques. Swing voters are more vulnerable to these propaganda techniques compared to non-swing voters, with differences in vulnerability patterns across various types of political shifts.
  arXiv  Detail & Related papers  (2024-07-01T13:34:29Z)
• Gender Differences in Abuse: The Case of Dutch Politicians on Twitter [0.10152838128195464]
  This paper analyses gender differences in abuse received by Dutch politicians on Twitter. All tweets directed at party leaders throughout the entire year of 2022 were collected. Female ethnic minority politicians received the highest levels of threats compared to all groups.
  arXiv  Detail & Related papers  (2023-06-19T08:23:24Z)
• Design and analysis of tweet-based election models for the 2021 Mexican legislative election [55.41644538483948]
  We use a dataset of 15 million election-related tweets in the six months preceding election day. We find that models using data with geographical attributes determine the results of the election with better precision and accuracy than conventional polling methods.
  arXiv  Detail & Related papers  (2023-01-02T12:40:05Z)
• Novelty in news search: a longitudinal study of the 2020 US elections [62.997667081978825]
  We analyze novelty, a measurement of new items that emerge in the top news search results. We find more new items emerging for election related queries compared to topical or stable queries. We argue that such imbalances affect the visibility of political candidates in news searches during electoral periods.
  arXiv  Detail & Related papers  (2022-11-09T08:42:37Z)
• Manipulating Twitter Through Deletions [64.33261764633504]
  Research into influence campaigns on Twitter has mostly relied on identifying malicious activities from tweets obtained via public APIs. Here, we provide the first exhaustive, large-scale analysis of anomalous deletion patterns involving more than a billion deletions by over 11 million accounts. We find that a small fraction of accounts delete a large number of tweets daily. First, limits on tweet volume are circumvented, allowing certain accounts to flood the network with over 26 thousand daily tweets. Second, coordinated networks of accounts engage in repetitive likes and unlikes of content that is eventually deleted, which can manipulate ranking algorithms.
  arXiv  Detail & Related papers  (2022-03-25T20:07:08Z)
• Shifting Polarization and Twitter News Influencers between two U.S. Presidential Elections [92.33485580547801]
  We analyze the change of polarization between the 2016 and 2020 U.S. presidential elections. Most of the top influencers were affiliated with media organizations during both elections. 75% of the top influencers in 2020 were not present in 2016, demonstrating that such status is difficult to retain.
  arXiv  Detail & Related papers  (2021-11-03T20:08:54Z)
• Reaching the bubble may not be enough: news media role in online political polarization [58.720142291102135]
  A way of reducing polarization would be by distributing cross-partisan news among individuals with distinct political orientations. This study investigates whether this holds in the context of nationwide elections in Brazil and Canada.
  arXiv  Detail & Related papers  (2021-09-18T11:34:04Z)
• 2020 U.S. Presidential Election: Analysis of Female and Male Users on Twitter [8.651122862855495]
  Current literature mainly focuses on analyzing the content of tweets without considering the gender of users. This research collects and analyzes a large number of tweets posted during the 2020 U.S. presidential election. Our findings are based upon a wide range of topics, such as tax, climate change, and the COVID-19 pandemic.
  arXiv  Detail & Related papers  (2021-08-21T01:31:03Z)
• MP Twitter Engagement and Abuse Post-first COVID-19 Lockdown in the UK: White Paper [1.9830978436021898]
  This work covers the period of June to December 2020 and analyses Twitter abuse in replies to UK MPs. We have found that abuse levels toward UK MPs were at an all-time high in December 2020 (5.4% of all reply tweets sent to MPs) In a departure from the trend seen in the first four months of the pandemic, MPs from the Tory party received the highest percentage of abusive replies from July 2020 onward.
  arXiv  Detail & Related papers  (2021-03-04T09:45:00Z)
• Towards Measuring Adversarial Twitter Interactions against Candidates in the US Midterm Elections [25.374045377135307]
  We measure the adversarial interactions against candidates for the US House of Representatives during the run-up to the 2018 US general election. We develop a new technique for detecting tweets with toxic content that are directed at any specific candidate. We use these techniques to outline the breadth of adversarial interactions seen in the election, including offensive name-calling, threats of violence, posting discrediting information, attacks on identity, and adversarial message repetition.
  arXiv  Detail & Related papers  (2020-05-09T10:00:41Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.