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  • Influence
Cyber Hate Speech on Twitter: An Application of Machine Classification and Statistical Modeling for Policy and Decision Making
It is demonstrated how the results of the classifier can be robustly utilized in a statistical model used to forecast the likely spread of cyber hate in a sample of Twitter data. Expand
Researching online populations: the use of online focus groups for social research
The survivability of ‘traditional’ methods within computer-mediated settings is dependent upon their capacity to be utilized and adapted to the technology that mediates human interaction online. ThisExpand
Who Tweets? Deriving the Demographic Characteristics of Age, Occupation and Social Class from Twitter User Meta-Data
The age detection tool illustrates the youthfulness of Twitter users compared to the general UK population as of the 2011 Census according to proportions, but projections demonstrate that there is still potentially a large number of older platform users. Expand
Us and them: identifying cyber hate on Twitter across multiple protected characteristics
This work uses text parsing to extract typed dependencies, which represent syntactic and grammatical relationships between words, and are shown to capture ‘othering’ language - consistently improving machine classification for different types of cyber hate beyond the use of a Bag of Words and known hateful terms. Expand
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 mediaExpand
Avatar watching: participant observation in graphical online environments
It is concluded that the advent of new broadband technologies and the expansion of graphical online environments require online methods that are both responsive and adaptive in order to elicit reliable and valid data from rapidly changing online environments. Expand
Tweeting the terror: modelling the social media reaction to the Woolwich terrorist attack
Novel findings are reported that identify that the sentiment expressed in the tweet is statistically significantly predictive of both size and survival of information flows of this nature. Expand
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 byExpand
Digital social research, social media and the sociological imagination: surrogacy, augmentation and re-orientation
Technological innovation in digital communications, epitomised in the shift from the informational web (Web1.0) to the interactional web (Web2.0), provokes new opportunities and challenges for socialExpand
140 Characters to Victory?: Using Twitter to Predict the UK 2015 General Election
This paper uses Twitter data to forecast the outcome of the 2015 UK General Election and develops a ‘baseline’ model of prediction that incorporates sentiment analysis and prior party support to generate a true forecast of parliament seat allocation. Expand