Abstract
| Original language | English |
|---|---|
| Journal | PLoS ONE |
| Volume | 10 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2015 |
Keywords
- adult
- aged
- Article
- crime victim
- data processing
- homicide
- human
- legal evidence
- middle aged
- online system
- perception
- public opinion
- publication
- social media
- social network
- space and space related phenomena
- time of death
- United States
- young adult
- crime
- England
- spatial analysis
- statistical model
- theoretical model
- time factor
- Crime
- Homicide
- Humans
- Likelihood Functions
- London
- Models, Theoretical
- Public Opinion
- Social Media
- Spatial Analysis
- Time Factors
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In: PLoS ONE, Vol. 10, No. 3, 2015.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Exploring Twitter to Analyze the Public’s Reaction Patterns to Recently Reported Homicides in London
AU - Kounadi, O.
AU - Lampoltshammer, T.J.
AU - Groff, E.
AU - Sitko, I.
AU - Leitner, M.
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PY - 2015
Y1 - 2015
N2 - Crime is an ubiquitous part of society. The way people express their concerns about crimes has been of particular interest to the scientific community. Over time, the numbers and kinds of available communication channels have increased. Today, social media services, such Twitter, present a convenient way to express opinions and concerns about crimes. The main objective of this study is to explore people's perception of homicides, specifically, how the characteristics and proximity of the event affect the public's concern about it. The analysis explores Twitter messages that refer to homicides that occurred in London in 2012. In particular, the dependence of tweeting propensity on the proximity, in space and time, of a crime incident and of people being concerned about that particular incident are examined. Furthermore, the crime characteristics of the homicides are analysed using logistic regression analysis. The results show that the proximity of the Twitter users' estimated home locations to the homicides' locations impacts on whether the associated crime news is spread or not and how quickly. More than half of the homicide related tweets are sent within the first week and the majority of them are sent within a month of the incident's occurrence. Certain crime characteristics, including the presence of a knife, a young victim, a British victim, or a homicide committed by a gang are predictors of the crime-tweets posting frequency. © 2015 Kounadi et al.
AB - Crime is an ubiquitous part of society. The way people express their concerns about crimes has been of particular interest to the scientific community. Over time, the numbers and kinds of available communication channels have increased. Today, social media services, such Twitter, present a convenient way to express opinions and concerns about crimes. The main objective of this study is to explore people's perception of homicides, specifically, how the characteristics and proximity of the event affect the public's concern about it. The analysis explores Twitter messages that refer to homicides that occurred in London in 2012. In particular, the dependence of tweeting propensity on the proximity, in space and time, of a crime incident and of people being concerned about that particular incident are examined. Furthermore, the crime characteristics of the homicides are analysed using logistic regression analysis. The results show that the proximity of the Twitter users' estimated home locations to the homicides' locations impacts on whether the associated crime news is spread or not and how quickly. More than half of the homicide related tweets are sent within the first week and the majority of them are sent within a month of the incident's occurrence. Certain crime characteristics, including the presence of a knife, a young victim, a British victim, or a homicide committed by a gang are predictors of the crime-tweets posting frequency. © 2015 Kounadi et al.
KW - adult
KW - aged
KW - Article
KW - crime victim
KW - data processing
KW - homicide
KW - human
KW - legal evidence
KW - middle aged
KW - online system
KW - perception
KW - public opinion
KW - publication
KW - social media
KW - social network
KW - space and space related phenomena
KW - time of death
KW - United States
KW - young adult
KW - crime
KW - England
KW - spatial analysis
KW - statistical model
KW - theoretical model
KW - time factor
KW - Crime
KW - Homicide
KW - Humans
KW - Likelihood Functions
KW - London
KW - Models, Theoretical
KW - Public Opinion
KW - Social Media
KW - Spatial Analysis
KW - Time Factors
U2 - 10.1371/journal.pone.0121848
DO - 10.1371/journal.pone.0121848
M3 - Article
SN - 1932-6203
VL - 10
JO - PLoS ONE
JF - PLoS ONE
IS - 3
ER -