Pete Burnap
Biographic Data
| ID | 288699 |
|---|---|
| NAME | Pete Burnap |
| GIVEN NAMES | Pete |
| FAMILY NAME | Burnap |
| SIGNATURE | BURNAP P |
| AFFILIATIONS | Cardiff University |
| ORCID | 0000-0003-0396-633X |
| VERIFIED | Yes |
| TOTAL WORKS | 22 |
| TOTAL CITATIONS | 222 |
| AUTHOR COUNT | 22 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 9 |
The Effect of the Brexit Vote on the Variation in Race and Religious Hate Crimes in England, Wales, Scotland and Northern Ireland
This paper examines possible mechanisms behind the spike in racially or religiously-aggravated (RR) offences after the Brexit vote. It adds to the current literature in five significant ways: (1) it provides the first Brexit-related RR hate crime comparison between England and Wales, Scotland and Northern Ireland; (2) it reports on results from a national-level panel model that adds to the debate in the literature on whether pro-leave or pro-rema…
Disrupting drive-by download networks on Twitter
This paper tests disruption strategies in Twitter networks containing malicious URLs used in drive-by download attacks. Cybercriminals use popular events that attract a large number of Twitter users to infect and propagate malware by using trending hashtags and creating misleading tweets to lure users to malicious webpages. Due to Twitter’s 280 character restriction and automatic shortening of URLs, it is particularly susceptible to the propagati…
Disrupting networks of hate: Characterising Hateful Networks and Removing Critical Nodes
Hateful individuals and groups have increasingly been using the Internet to express their ideas, spread their beliefs and recruit new members. Understanding the network characteristics of these hateful groups could help understand individuals' exposure to hate and derive intervention strategies to mitigate the dangers of such networks by disrupting communications. This article analyses two hateful followers' networks and three hateful retweet net…
Antisemitism on Twitter: Collective Efficacy and the Role of Community Organisations in Challenging Online Hate Speech
In this article, we conduct a comprehensive study of online antagonistic content related to Jewish identity posted on Twitter between October 2015 and October 2016 by UK-based users. We trained a scalable supervised machine learning classifier to identify antisemitic content to reveal patterns of online antisemitism perpetration at the source. We built statistical models to analyze the inhibiting and enabling factors of the size (number of retwee…
Linking Twitter and Survey Data: The Impact of Survey Mode and Demographics on Consent Rates Across Three UK Studies
In light of issues such as increasing unit nonresponse in surveys, several studies argue that social media sources such as Twitter can be used as a viable alternative. However, there are also a number of shortcomings with Twitter data such as questions about its representativeness of the wider population and the inability to validate whose data you are collecting. A useful way forward could be to combine survey and Twitter data to supplement and …
Are youth suicide memorial sites on Facebook different from those for other sudden deaths
To explore possible distinctive features of online memorials for youth suicides, amid concerns about glorification, we compared public Facebook memorials for suicides and road traffic accident deaths, using Linguistic Inquiry and Word Count software. People who posted on memorial sites wrote at greater length about suicides, using longer words and more quotation marks. Words suggesting causation and achievement were more prevalent in suicide memo…
Hate in the Machine: Anti-Black and Anti-Muslim Social Media Posts as Predictors of Offline Racially and Religiously Aggravated Crime
National governments now recognize online hate speech as a pernicious social problem. In the wake of political votes and terror attacks, hate incidents online and offline are known to peak in tandem. This article examines whether an association exists between both forms of hate, independent of ‘trigger’ events. Using Computational Criminology that draws on data science methods, we link police crime, census and Twitter data to establish a temporal…
Under the Corporate Radar: Examining Insider Business Cybercrime Victimization through an Application of Routine Activities Theory
Cybercrime is recognized as one of the top threats to UK economic security. On a daily basis, the computer networks of businesses suffer security breaches. A less explored dimension of this problem is cybercrimes committed by insiders. This paper provides a criminological analysis of corporate insider victimization. It begins by presenting reviews of insider criminal threats and routine activities theory as applied to cybercrime. Analysis of the …
Interaction and Transformation on Social Media: The Case of Twitter Campaigns
The increasing popularity of social media platforms creates new digital social networks in which individuals can interact and share information, news, and opinion. The use of these technologies appears to have the capacity to transform current social configurations and relations, not least within the public and civic spheres. Within the social sciences, much emphasis has been placed on conceptualizing social media's role in modern society and the…
Towards an Ethical Framework for Publishing Twitter Data in Social Research: Taking into Account Users' Views, Online Context and Algorithmic Estimation
New and emerging forms of data, including posts harvested from social media sites such as Twitter, have become part of the sociologist's data diet. In particular, some researchers see an advantage in the perceived 'public' nature of Twitter posts, representing them in publications without seeking informed consent. While such practice may not be at odds with Twitter's terms of service, we argue there is a need to interpret these through the lens o…
Digital wildfires: Hyper-Connectivity, Havoc and a Global Ethos to Govern Social Media
The last 5--10 years have seen a massive rise in the popularity of social media platforms such as Twitter, Facebook, Tumblr etc. These platforms enable users to post and share their own content instantly, meaning that material can be seen by multiple others in a short period of time. The growing use of social media has been accompanied by concerns that these platforms enable the rapid and global spread of harmful content. A report by the World Ec…
Crime Sensing with Big Data: The Affordances and Limitations of using Open Source Communications to Estimate Crime Patterns
This paper critically examines the affordances and limitations of big data for the study of crime and disorder. We hypothesize that disorder-related posts on Twitter are associated with actual police crime rates. Our results provide evidence that naturally occurring social media data may provide an alternative information source on the crime problem. This paper adds to the emerging field of computational criminology and big data in four ways: (1)…
Cyberhate on Social Media in the aftermath of Woolwich: A Case Study in Computational Criminology and Big Data
This paper presents the first criminological analysis of an online social reaction to a crime event of national significance, in particular the detection and propagation of cyberhate on social media following a terrorist attack. We take the Woolwich, London terrorist attack in 2013 as our event of interest and draw on Cohen’s process of warning, impact, inventory and reaction to delineate a sequence of incidents that come to constitute a series o…
Characters to Victory: Using Twitter to predict the UK 2015 General Election
Who Tweets? Deriving the Demographic Characteristics of Age, Occupation and Social Class from Twitter User Meta-Data
This paper specifies, designs and critically evaluates two tools for the automated identification of demographic data (age, occupation and social class) from the profile descriptions of Twitter users in the United Kingdom (UK). Meta-data data routinely collected through the Collaborative Social Media Observatory (COSMOS: http://www.cosmosproject.net/) relating to UK Twitter users is matched with the occupational lookup tables between job and soci…
Cyber Hate Speech on Twitter: An Application of Machine Classification and Statistical Modeling for Policy and Decision Making
The use of “Big Data” in policy and decision making is a current topic of debate. The 2013 murder of Drummer Lee Rigby in Woolwich, London, UK led to an extensive public reaction on social media, providing the opportunity to study the spread of online hate speech (cyber hate) on Twitter. Human annotated Twitter data was collected in the immediate aftermath of Rigby's murder to train and test a supervised machine learning text classifier that dist…
Big and broad social data and the sociological imagination: A collaborative response
In this paper, we reflect on the disciplinary contours of contemporary sociology, and social science more generally, in the age of ‘big and broad’ social data. Our aim is to suggest how sociology and social sciences may respond to the challenges and opportunities presented by this ‘data deluge’ in ways that are innovative yet sensitive to the social and ethical life of data and methods. We begin by reviewing relevant contemporary methodological d…
Tweeting the terror: Modelling the social media reaction to the Woolwich terrorist attack
Little is currently known about the factors that promote the propagation of information in online social networks following terrorist events. In this paper we took the case of the terrorist event in Woolwich, London in 2013 and built models to predict information flow size and survival using data derived from the popular social networking site Twitter. We define information flows as the propagation over time of information posted to Twitter via t…
Making sense of self-reported socially significant data using computational methods
The growing number of people using social media to communicate with their peers and document their personal everyday feelings and views is creating a ‘data on an epic scale’ that provides the opportunity for social scientists to conduct research such as ethnography, discourse and content analysis of social interactions, providing an additional insight into today’s society. However, the tools and methods required to conduct such analysis are often…
Policing cyber-neighbourhoods: Tension monitoring and social media networks
We propose that late modern policing practices, that rely on neighbourhood intelligence, the monitoring of tensions, surveillance and policing by accommodation, need to be augmented in light of emerging ‘cyber-neighbourhoods’, namely social media networks. The 2011 riots in England were the first to evidence the widespread use of social media platforms to organise and respond to disorder. The police were ill-equipped to make use of the intelligen…
Knowing the Tweeters: Deriving Sociologically Relevant Demographics from Twitter
A perennial criticism regarding the use of social media in social science research is the lack of demographic information associated with naturally occurring mediated data such as that produced by Twitter. However the fact that demographics information is not explicit does not mean that it is not implicitly present. Utilising the Cardiff Online Social Media ObServatory (COSMOS) this paper suggests various techniques for establishing or estimating…
Sintero server scalable interoperability framework for Dallas communities
We describe a prototype open source UK-scalable Health Information Exchange (HIE) to support patient-centric care, translational research and other secondary uses. It has been designed by interoperability experts to standardise information flows across the patient path-for example from home, work, mobile, clinical and community care locations. Sintero enables secure information sharing within the patient's named 'circle of care' including family,…
Towards an Ethical Framework for Publishing Twitter Data in Social Research: Taking into Account Users' Views, Online Context and Algorithmic Estimation
New and emerging forms of data, including posts harvested from social media sites such as Twitter, have become part of the sociologist's data diet. In particular, some researchers see an advantage in the perceived 'public' nature of Twitter posts, representing them in publications without seeking informed consent. While such practice may not be at odds with Twitter's terms of service, we argue there is a need to interpret these through the lens o…
Characters to Victory: Using Twitter to predict the UK 2015 General Election
Big and broad social data and the sociological imagination: A collaborative response
In this paper, we reflect on the disciplinary contours of contemporary sociology, and social science more generally, in the age of ‘big and broad’ social data. Our aim is to suggest how sociology and social sciences may respond to the challenges and opportunities presented by this ‘data deluge’ in ways that are innovative yet sensitive to the social and ethical life of data and methods. We begin by reviewing relevant contemporary methodological d…
Cyberhate on Social Media in the aftermath of Woolwich: A Case Study in Computational Criminology and Big Data
This paper presents the first criminological analysis of an online social reaction to a crime event of national significance, in particular the detection and propagation of cyberhate on social media following a terrorist attack. We take the Woolwich, London terrorist attack in 2013 as our event of interest and draw on Cohen’s process of warning, impact, inventory and reaction to delineate a sequence of incidents that come to constitute a series o…
Policing cyber-neighbourhoods: Tension monitoring and social media networks
We propose that late modern policing practices, that rely on neighbourhood intelligence, the monitoring of tensions, surveillance and policing by accommodation, need to be augmented in light of emerging ‘cyber-neighbourhoods’, namely social media networks. The 2011 riots in England were the first to evidence the widespread use of social media platforms to organise and respond to disorder. The police were ill-equipped to make use of the intelligen…
Tweeting the terror: Modelling the social media reaction to the Woolwich terrorist attack
Little is currently known about the factors that promote the propagation of information in online social networks following terrorist events. In this paper we took the case of the terrorist event in Woolwich, London in 2013 and built models to predict information flow size and survival using data derived from the popular social networking site Twitter. We define information flows as the propagation over time of information posted to Twitter via t…
Knowing the Tweeters: Deriving Sociologically Relevant Demographics from Twitter
A perennial criticism regarding the use of social media in social science research is the lack of demographic information associated with naturally occurring mediated data such as that produced by Twitter. However the fact that demographics information is not explicit does not mean that it is not implicitly present. Utilising the Cardiff Online Social Media ObServatory (COSMOS) this paper suggests various techniques for establishing or estimating…
Linking Twitter and Survey Data: The Impact of Survey Mode and Demographics on Consent Rates Across Three UK Studies
In light of issues such as increasing unit nonresponse in surveys, several studies argue that social media sources such as Twitter can be used as a viable alternative. However, there are also a number of shortcomings with Twitter data such as questions about its representativeness of the wider population and the inability to validate whose data you are collecting. A useful way forward could be to combine survey and Twitter data to supplement and …
Under the Corporate Radar: Examining Insider Business Cybercrime Victimization through an Application of Routine Activities Theory
Cybercrime is recognized as one of the top threats to UK economic security. On a daily basis, the computer networks of businesses suffer security breaches. A less explored dimension of this problem is cybercrimes committed by insiders. This paper provides a criminological analysis of corporate insider victimization. It begins by presenting reviews of insider criminal threats and routine activities theory as applied to cybercrime. Analysis of the …
Hate in the Machine: Anti-Black and Anti-Muslim Social Media Posts as Predictors of Offline Racially and Religiously Aggravated Crime
National governments now recognize online hate speech as a pernicious social problem. In the wake of political votes and terror attacks, hate incidents online and offline are known to peak in tandem. This article examines whether an association exists between both forms of hate, independent of ‘trigger’ events. Using Computational Criminology that draws on data science methods, we link police crime, census and Twitter data to establish a temporal…
Crime Sensing with Big Data: The Affordances and Limitations of using Open Source Communications to Estimate Crime Patterns
This paper critically examines the affordances and limitations of big data for the study of crime and disorder. We hypothesize that disorder-related posts on Twitter are associated with actual police crime rates. Our results provide evidence that naturally occurring social media data may provide an alternative information source on the crime problem. This paper adds to the emerging field of computational criminology and big data in four ways: (1)…
The Effect of the Brexit Vote on the Variation in Race and Religious Hate Crimes in England, Wales, Scotland and Northern Ireland
This paper examines possible mechanisms behind the spike in racially or religiously-aggravated (RR) offences after the Brexit vote. It adds to the current literature in five significant ways: (1) it provides the first Brexit-related RR hate crime comparison between England and Wales, Scotland and Northern Ireland; (2) it reports on results from a national-level panel model that adds to the debate in the literature on whether pro-leave or pro-rema…
Making sense of self-reported socially significant data using computational methods
The growing number of people using social media to communicate with their peers and document their personal everyday feelings and views is creating a ‘data on an epic scale’ that provides the opportunity for social scientists to conduct research such as ethnography, discourse and content analysis of social interactions, providing an additional insight into today’s society. However, the tools and methods required to conduct such analysis are often…
Interaction and Transformation on Social Media: The Case of Twitter Campaigns
The increasing popularity of social media platforms creates new digital social networks in which individuals can interact and share information, news, and opinion. The use of these technologies appears to have the capacity to transform current social configurations and relations, not least within the public and civic spheres. Within the social sciences, much emphasis has been placed on conceptualizing social media's role in modern society and the…
Disrupting networks of hate: Characterising Hateful Networks and Removing Critical Nodes
Hateful individuals and groups have increasingly been using the Internet to express their ideas, spread their beliefs and recruit new members. Understanding the network characteristics of these hateful groups could help understand individuals' exposure to hate and derive intervention strategies to mitigate the dangers of such networks by disrupting communications. This article analyses two hateful followers' networks and three hateful retweet net…
Antisemitism on Twitter: Collective Efficacy and the Role of Community Organisations in Challenging Online Hate Speech
In this article, we conduct a comprehensive study of online antagonistic content related to Jewish identity posted on Twitter between October 2015 and October 2016 by UK-based users. We trained a scalable supervised machine learning classifier to identify antisemitic content to reveal patterns of online antisemitism perpetration at the source. We built statistical models to analyze the inhibiting and enabling factors of the size (number of retwee…
Sintero server scalable interoperability framework for Dallas communities
We describe a prototype open source UK-scalable Health Information Exchange (HIE) to support patient-centric care, translational research and other secondary uses. It has been designed by interoperability experts to standardise information flows across the patient path-for example from home, work, mobile, clinical and community care locations. Sintero enables secure information sharing within the patient's named 'circle of care' including family,…
Making sense of self-reported socially significant data using computational methods
The growing number of people using social media to communicate with their peers and document their personal everyday feelings and views is creating a ‘data on an epic scale’ that provides the opportunity for social scientists to conduct research such as ethnography, discourse and content analysis of social interactions, providing an additional insight into today’s society. However, the tools and methods required to conduct such analysis are often…
Policing cyber-neighbourhoods: Tension monitoring and social media networks
We propose that late modern policing practices, that rely on neighbourhood intelligence, the monitoring of tensions, surveillance and policing by accommodation, need to be augmented in light of emerging ‘cyber-neighbourhoods’, namely social media networks. The 2011 riots in England were the first to evidence the widespread use of social media platforms to organise and respond to disorder. The police were ill-equipped to make use of the intelligen…
Knowing the Tweeters: Deriving Sociologically Relevant Demographics from Twitter
A perennial criticism regarding the use of social media in social science research is the lack of demographic information associated with naturally occurring mediated data such as that produced by Twitter. However the fact that demographics information is not explicit does not mean that it is not implicitly present. Utilising the Cardiff Online Social Media ObServatory (COSMOS) this paper suggests various techniques for establishing or estimating…
Big and broad social data and the sociological imagination: A collaborative response
In this paper, we reflect on the disciplinary contours of contemporary sociology, and social science more generally, in the age of ‘big and broad’ social data. Our aim is to suggest how sociology and social sciences may respond to the challenges and opportunities presented by this ‘data deluge’ in ways that are innovative yet sensitive to the social and ethical life of data and methods. We begin by reviewing relevant contemporary methodological d…
Tweeting the terror: Modelling the social media reaction to the Woolwich terrorist attack
Little is currently known about the factors that promote the propagation of information in online social networks following terrorist events. In this paper we took the case of the terrorist event in Woolwich, London in 2013 and built models to predict information flow size and survival using data derived from the popular social networking site Twitter. We define information flows as the propagation over time of information posted to Twitter via t…
Who Tweets? Deriving the Demographic Characteristics of Age, Occupation and Social Class from Twitter User Meta-Data
This paper specifies, designs and critically evaluates two tools for the automated identification of demographic data (age, occupation and social class) from the profile descriptions of Twitter users in the United Kingdom (UK). Meta-data data routinely collected through the Collaborative Social Media Observatory (COSMOS: http://www.cosmosproject.net/) relating to UK Twitter users is matched with the occupational lookup tables between job and soci…
Cyber Hate Speech on Twitter: An Application of Machine Classification and Statistical Modeling for Policy and Decision Making
The use of “Big Data” in policy and decision making is a current topic of debate. The 2013 murder of Drummer Lee Rigby in Woolwich, London, UK led to an extensive public reaction on social media, providing the opportunity to study the spread of online hate speech (cyber hate) on Twitter. Human annotated Twitter data was collected in the immediate aftermath of Rigby's murder to train and test a supervised machine learning text classifier that dist…
Digital wildfires: Hyper-Connectivity, Havoc and a Global Ethos to Govern Social Media
The last 5--10 years have seen a massive rise in the popularity of social media platforms such as Twitter, Facebook, Tumblr etc. These platforms enable users to post and share their own content instantly, meaning that material can be seen by multiple others in a short period of time. The growing use of social media has been accompanied by concerns that these platforms enable the rapid and global spread of harmful content. A report by the World Ec…
Crime Sensing with Big Data: The Affordances and Limitations of using Open Source Communications to Estimate Crime Patterns
This paper critically examines the affordances and limitations of big data for the study of crime and disorder. We hypothesize that disorder-related posts on Twitter are associated with actual police crime rates. Our results provide evidence that naturally occurring social media data may provide an alternative information source on the crime problem. This paper adds to the emerging field of computational criminology and big data in four ways: (1)…
Cyberhate on Social Media in the aftermath of Woolwich: A Case Study in Computational Criminology and Big Data
This paper presents the first criminological analysis of an online social reaction to a crime event of national significance, in particular the detection and propagation of cyberhate on social media following a terrorist attack. We take the Woolwich, London terrorist attack in 2013 as our event of interest and draw on Cohen’s process of warning, impact, inventory and reaction to delineate a sequence of incidents that come to constitute a series o…
Characters to Victory: Using Twitter to predict the UK 2015 General Election
Towards an Ethical Framework for Publishing Twitter Data in Social Research: Taking into Account Users' Views, Online Context and Algorithmic Estimation
New and emerging forms of data, including posts harvested from social media sites such as Twitter, have become part of the sociologist's data diet. In particular, some researchers see an advantage in the perceived 'public' nature of Twitter posts, representing them in publications without seeking informed consent. While such practice may not be at odds with Twitter's terms of service, we argue there is a need to interpret these through the lens o…
Interaction and Transformation on Social Media: The Case of Twitter Campaigns
The increasing popularity of social media platforms creates new digital social networks in which individuals can interact and share information, news, and opinion. The use of these technologies appears to have the capacity to transform current social configurations and relations, not least within the public and civic spheres. Within the social sciences, much emphasis has been placed on conceptualizing social media's role in modern society and the…
Linking Twitter and Survey Data: The Impact of Survey Mode and Demographics on Consent Rates Across Three UK Studies
In light of issues such as increasing unit nonresponse in surveys, several studies argue that social media sources such as Twitter can be used as a viable alternative. However, there are also a number of shortcomings with Twitter data such as questions about its representativeness of the wider population and the inability to validate whose data you are collecting. A useful way forward could be to combine survey and Twitter data to supplement and …
Are youth suicide memorial sites on Facebook different from those for other sudden deaths
To explore possible distinctive features of online memorials for youth suicides, amid concerns about glorification, we compared public Facebook memorials for suicides and road traffic accident deaths, using Linguistic Inquiry and Word Count software. People who posted on memorial sites wrote at greater length about suicides, using longer words and more quotation marks. Words suggesting causation and achievement were more prevalent in suicide memo…
Hate in the Machine: Anti-Black and Anti-Muslim Social Media Posts as Predictors of Offline Racially and Religiously Aggravated Crime
National governments now recognize online hate speech as a pernicious social problem. In the wake of political votes and terror attacks, hate incidents online and offline are known to peak in tandem. This article examines whether an association exists between both forms of hate, independent of ‘trigger’ events. Using Computational Criminology that draws on data science methods, we link police crime, census and Twitter data to establish a temporal…
Under the Corporate Radar: Examining Insider Business Cybercrime Victimization through an Application of Routine Activities Theory
Cybercrime is recognized as one of the top threats to UK economic security. On a daily basis, the computer networks of businesses suffer security breaches. A less explored dimension of this problem is cybercrimes committed by insiders. This paper provides a criminological analysis of corporate insider victimization. It begins by presenting reviews of insider criminal threats and routine activities theory as applied to cybercrime. Analysis of the …
Antisemitism on Twitter: Collective Efficacy and the Role of Community Organisations in Challenging Online Hate Speech
In this article, we conduct a comprehensive study of online antagonistic content related to Jewish identity posted on Twitter between October 2015 and October 2016 by UK-based users. We trained a scalable supervised machine learning classifier to identify antisemitic content to reveal patterns of online antisemitism perpetration at the source. We built statistical models to analyze the inhibiting and enabling factors of the size (number of retwee…
Disrupting drive-by download networks on Twitter
This paper tests disruption strategies in Twitter networks containing malicious URLs used in drive-by download attacks. Cybercriminals use popular events that attract a large number of Twitter users to infect and propagate malware by using trending hashtags and creating misleading tweets to lure users to malicious webpages. Due to Twitter’s 280 character restriction and automatic shortening of URLs, it is particularly susceptible to the propagati…
Disrupting networks of hate: Characterising Hateful Networks and Removing Critical Nodes
Hateful individuals and groups have increasingly been using the Internet to express their ideas, spread their beliefs and recruit new members. Understanding the network characteristics of these hateful groups could help understand individuals' exposure to hate and derive intervention strategies to mitigate the dangers of such networks by disrupting communications. This article analyses two hateful followers' networks and three hateful retweet net…
The Effect of the Brexit Vote on the Variation in Race and Religious Hate Crimes in England, Wales, Scotland and Northern Ireland
This paper examines possible mechanisms behind the spike in racially or religiously-aggravated (RR) offences after the Brexit vote. It adds to the current literature in five significant ways: (1) it provides the first Brexit-related RR hate crime comparison between England and Wales, Scotland and Northern Ireland; (2) it reports on results from a national-level panel model that adds to the debate in the literature on whether pro-leave or pro-rema…
Computer Science (18 works) · Social media (15 works) · Sociology (13 works) · Political science (12 works) · World Wide Web (12 works) · Law (9 works) · Social Media and Politics (9 works) · Criminology (7 works) · Hate Speech and Cyberbullying Detection (7 works) · Internet privacy (7 works)