Does news coverage of traffic crashes affect perceived blame and preferred solutions? Evidence from an experiment

Goddard, Tara; Ralph, Kelcie; Thigpen, Calvin; Iacobucci, Evan

doi:10.1016/j.trip.2019.100073

Cited by 22 publications

(26 citation statements)

References 22 publications

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“…19 A consequence of focusing on the specific collisions rather than structural causes behind RTCs may be that readers blame driver behaviour rather than the environment. 20 This may reduce the onus on policy makers to employ systematic solutions to RTCs. However, the majority of SA-8 articles were written by The Times of India, suggesting that training The Times of India journalists may influence overall coverage of RTCs.…”

Section: Bmj Global Healthmentioning

confidence: 99%

Media coverage and framing of road traffic safety in India

et al. 2021

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BackgroundMedia coverage of road traffic collisions (RTCs) may influence preventative action. India experiences some of the highest RTC mortality and morbidity rates globally, but advocacy and effective action to mitigate this has been limited. We conducted an analysis of Indian media in English to assess whether coverage met the WHO’s Reporting on Road Safety guidelines for evidence-based reporting of RTCs.MethodsEnglish-language articles published online between March 2018 and February 2019 were assessed against the seven recommended story angles and seven recommended key elements in the WHO guidelines.Results458 articles were included in the analysis. The most common story angle was descriptions of single collisions, which was not a WHO-recommended story angle. These included limited key elements such as use of human story or linking to road safety risks or evidence-based solutions. However, some articles did follow the WHO-recommended story angles, with 22.1% discussing specific road safety solutions and a further 6.3% discussing vulnerable groups. Almost all articles avoided the use of technical language, but only 2.0% explicitly stated that RTCs were preventable. More than half identified at least one evidence-based solution. Very few articles discussed economic or health impacts of RTCs, including the burden they present to the public health system.ConclusionIndian media in English can improve reporting by focusing on human stories and documenting experiences of those injured in RTCs. Coverage should also focus more on evidence-based solutions, emphasising the systems approach which encourages government action rather than changes to individual behaviour.

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Section: Bmj Global Healthmentioning

confidence: 99%

Media coverage and framing of road traffic safety in India

et al. 2021

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“…After the lanes opened, traditional media reported on the opening of the lanes ('Caution the word for Pandora bike lanes, opening Monday' @timescolonist 858358529434034179), confusion for car drivers ('Two wheeled elation, and four wheeled confusion as Victoria's protected bike lanes open on Pandora' @CTVNewsScott 859110144319397888) and an early crash ('Serious crash on Pandora bike lane raises flags' @timescolonist 872805264084287488). Framing and grammatical choices by media can influence public perception of crash responsibility (Goddard et al, 2019). These headlines and quotes may have been especially impactful, since they were broadly shared, quoted and discussed on Twitter, thus amplifying the attitudes purveyed by traditional media.…”

Section: Discussionmentioning

confidence: 99%

“…The Twitter search API provides a sample of Tweets that represents the most central accounts, thus missing activity from less central accounts (Gonza´lez-Bailo´n et al, 2014). While these peripheral accounts are less influential, they are more numerous, and they represent people who may be directly influenced by online discussions.…”

Section: Discussionmentioning

confidence: 99%

“…We chose the geographic keywords approach because it returned substantially more results than the geofence approach in our study areas. Twitter data retrieval is subject to internal filters that return a subset of data that is biased towards the most influential accounts (Gonza´lez-Bailo´n et al, 2014). Therefore, our analyses focus on the most central accounts in these discussions.…”

Section: Twitter Data Collectionmentioning

confidence: 99%

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From advocacy to acceptance: Social media discussions of protected bike lane installations

et al. 2020

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Many North American cities are building bicycling infrastructure. Lively discussions on social media, where people passionately support or reject bicycling infrastructure projects, provide a unique data set on attitudes towards bicycling infrastructure. Our goal is to analyse social media posts in Edmonton and Victoria, Canada as new bike infrastructure was implemented to understand the thematic and social elements of the conversation and how these changed over time. We collected Twitter messages ( n = 13,121: 7640 in Edmonton; 5481 in Victoria) and compared three timeframes: before lanes opened (January 2015 to lane opening); the first riding season (opening to April 2017); and the second riding season (May 2017 to November 2018). For each timeframe, we evaluated word-combination frequencies (to understand the use of language) and social network structures (to understand which accounts were influential and how they interacted). We observed a change in the three time periods. Before the bicycling infrastructure was built, Twitter activity was focused on advocacy, which was especially strong in Victoria. The first riding season had the most social media activity, the most diverse perspectives and the most controversy. The second riding season held more support. Based on the Twitter activity, we found that Edmonton had more support from local businesses and traditional media, launching a connected network of infrastructure with less social media opposition. Our results suggest that attitudes associated with change in bicycling infrastructure may have a cycle, with initial negative responses to change, followed by an uptick in positive attitudes.

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“…While providing prospective drivers with technology descriptions and idealized information regarding the AVs increases acceptance (Nees, 2016), news coverage of AV crashes has been shown to negatively impact the decisions to trust and rely on automation (Goddard et al, 2019;Jefferson & McDonald, 2019;Shariff et al, 2017). These findings suggest that adoption and safe use of AV technologies can be influenced by providing transparent information on AV capabilities and limitations.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach to Social Media Guideline Design and Its Application to Automated Vehicle Events

Alambeigi

Smith

Wei

et al. 2021

Proceedings of the Human Factors and Ergonomics Society Annual

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Public perception of and attitudes towards automated vehicle (AV) technologies significantly influence the acceptance and adoption of AVs. Users’ perceptions are increasingly driven by media exposure. Prior studies have observed that major news events such as crashes and technology announcements influence user responses to AVs. Guiding users’ expectations and exposure to information through accessible media resources should lead to calibrated expectations and appropriate use of automation, ultimately leading to fewer safety incidents. We used a two-component analysis of (1) AV event-related tweets, through topic modeling and sentiment analysis, and (2) subject-matter expert interviews, through thematic analysis, to design basic guidelines for AV communication. The use of these guidelines should increase public knowledge of AV capabilities and aid in the proper calibration of public trust and acceptance of AVs.

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Does news coverage of traffic crashes affect perceived blame and preferred solutions? Evidence from an experiment

Cited by 22 publications

References 22 publications

Media coverage and framing of road traffic safety in India

Media coverage and framing of road traffic safety in India

From advocacy to acceptance: Social media discussions of protected bike lane installations

A Novel Approach to Social Media Guideline Design and Its Application to Automated Vehicle Events

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