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 of social science research methods that imply a more reflexive ethical approach than provided in ‘legal’ accounts of the permissible use of these data in research publications. To challenge some existing practice in Twitter-based research, this article brings to the fore: (1) views of Twitter users through analysis of online survey data; (2) the effect of context collapse and online disinhibition on the behaviours of users; and (3) the publication of identifiable sensitive classifications derived from algorithms.
The NLRP3 inflammasome has recently emerged as an unexpected marker of stress and metabolic risk and has also been implicated in the development of major aging-related diseases such as gout, type 2 ...diabetes, obesity, cancer, and neurodegenerative and cardiovascular disorders. Several pathways regulating the NLRP3 inflammasome are currently being studied, but how the NLRP3 inflammasome is regulated remains unknown. AMP-activated protein kinase (AMPK), a central regulator of multiple metabolic pathways involved in the pathophysiology of aging and age-related diseases, has emerged as an important integrator of signals controlling inflammation including the inflammasome. In this Opinion article, we show that several AMPK-dependent pathways regulate NLRP3 inflammasome activation during aging, suggesting NLRP3 as a potential pharmacological target in age-related diseases.
AMP-activated protein kinase (AMPK) and the NLRP3 inflammasome are associated with aging and age-related diseases through the disturbance of metabolic and inflammatory pathways.
Many of the various NLRP3 inflammasome stimuli, such as mitochondrial and autophagy dysfunction and endoplasmic reticulum stress, become elevated during the aging process.
The AMPK–sirtuin 1 (SIRT1) axis could modulate the inhibition of NLRP3 by mitochondrial biogenesis and the induction of autophagy.
Inhibition of NLRP3 is also induced through various antiaging strategies such as metformin, rapamycin, or resveratrol treatment and caloric restriction.
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 distinguishes between hateful and/or antagonistic responses with a focus on race, ethnicity, or religion; and more general responses. Classification features were derived from the content of each tweet, including grammatical dependencies between words to recognize “othering” phrases, incitement to respond with antagonistic action, and claims of well‐founded or justified discrimination against social groups. The results of the classifier were optimal using a combination of probabilistic, rule‐based, and spatial‐based classifiers with a voted ensemble meta‐classifier. We demonstrate 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. The applications to policy and decision making are discussed.
Abstract
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 and spatial association between online hate speech that targets race and religion, and offline racially and religiously aggravated crimes in London over an eight-month period. The findings renew our understanding of hate crime as a process, rather than as a discrete event, for the digital age.
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 social class provided by the Office for National Statistics (ONS) using SOC2010. Using expert human validation, the validity and reliability of the automated matching process is critically assessed and a prospective class distribution of UK Twitter users is offered with 2011 Census baseline comparisons. The pattern matching rules for identifying age are explained and enacted following a discussion on how to minimise false positives. The age distribution of Twitter users, as identified using the tool, is presented alongside the age distribution of the UK population from the 2011 Census. The automated occupation detection tool reliably identifies certain occupational groups, such as professionals, for which job titles cannot be confused with hobbies or are used in common parlance within alternative contexts. An alternative explanation on the prevalence of hobbies is that the creative sector is overrepresented on Twitter compared to 2011 Census 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. It is possible to detect "signatures" of both occupation and age from Twitter meta-data with varying degrees of accuracy (particularly dependent on occupational groups) but further confirmatory work is needed.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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) it estimates the utility of social media data to explain variance in offline crime patterns; (2) it provides the first evidence of the estimation offline crime patterns using a measure of broken windows found in the textual content of social media communications; (3) it tests if the bias present in offline perceptions of disorder is present in online communications; and (4) it takes the results of experiments to critically engage with debates on big data and crime prediction.
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 of deviant responses following the attack. This paper adds to contemporary debates in criminology and the study of hate crime in three ways: (1) it provides the first analysis of the escalation, duration, diffusion and de-escalation of cyberhate in social media following a terrorist event; (2) it applies Cohen's work on action, reaction and amplification and the role of the traditional media to the online context and (3) it introduces and provides a case study in 'computational criminology'.
Online fraud is the most prevalent acquisitive crime in Europe. This study applies routine activities theory to a subset of online fraud, online identity theft, by exploring country-level mechanisms, ...in addition to individual determinants via a multi-level analysis of Eurobarometer survey data. This paper adds to the theory of cybercrime and policy debates by: (1) showing that country physical guardianship (e. g. cyber security strategy) moderates the effects of individual physical guardianship; (2) introducing a typology of online capable guardianship: passive physical, active personal and avoidance personal guardianship; (3) showing that online identity theft is associated with personal and physical guardianship; and (4) identifying public Internet access and online auction selling as highly risky routine activities. The paper concludes by emphasizing the importance of studying country-level effects on online identity theft victimization.
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