Now showing 1 - 10 of 13
- PublicationSocial complex contagion in music listenership: A natural experiment with 1.3 million participantsCan live music events generate complex contagion in music streaming? This paper finds evidence in the affirmative—but only for the most popular artists. We generate a novel dataset from a music tracking website to analyse the listenership history of 1.3 million users over a two-month time horizon. We show that attending a music artist's live concert increases that artist's listenership among the attendees of the concert by approximately 1 song per day per attendee (p-value < 0.001). Moreover, this effect is contagious and can spread to users who did not attend the event. However, whether or not contagion occurs depends on the type of artist. We only observe contagious increases in listenership for popular artists (∼0.06 more daily plays per friend of an attendee [p < 0.001]), while the effect is absent for emerging stars. The contagion effect size increases monotonically with the number of friends who have attended the live event.
139Scopus© Citations 8
- PublicationEmergence of world-stock-market networkForty stock market indices of the world with the highest GDP has been studied. We show each market is a part of a global structure, that we call “world-stock-market network”. Where the correlation between two markets is not independent of the correlation between two other markets. Towards this end, we analyze the cross-correlation matrix of the indices of these forty markets using Random Matrix Theory (RMT). We find the degree of collective behavior among the markets and the share of each market in the world global network. This finding together with the results obtained from the same calculation on four stock markets reinforces the idea of a world financial market. Finally, we draw the dendrogram of the cross-correlation matrix to make communities in this abstract global market visible. The results show that the world financial market comprises three communities each of which includes stock markets with geographical proximity.
140Scopus© Citations 16
- PublicationDetecting weak and strong Islamophobic hate speech on social mediaIslamophobic hate speech on social media is a growing concern in contemporary Western politics and society. It can inflict considerable harm on any victims who are targeted, create a sense of fear and exclusion amongst their communities, toxify public discourse and motivate other forms of extremist and hateful behavior. Accordingly, there is a pressing need for automated tools to detect and classify Islamophobic hate speech robustly and at scale, thereby enabling quantitative analyses of large textual datasets, such as those collected from social media. Previous research has mostly approached the automated detection of hate speech as a binary task. However, the varied nature of Islamophobia means that this is often inappropriate for both theoretically informed social science and effective monitoring of social media platforms. Drawing on in-depth conceptual work we build an automated software tool which distinguishes between non-Islamophobic, weak Islamophobic and strong Islamophobic content. Accuracy is 77.6% and balanced accuracy is 83%. Our tool enables future quantitative research into the drivers, spread, prevalence and effects of Islamophobic hate speech on social media.
477Scopus© Citations 72
- PublicationGender Imbalance and Spatiotemporal Patterns of Contributions to Citizen Science Projects: The Case of ZooniverseCitizen Science is research undertaken by professional scientists and members of the public collaboratively. Despite numerous benefits of citizen science for both the advancement of science and the community of the citizen scientists, there is still no comprehensive knowledge of patterns of contributions, and the demography of contributors to citizen science projects. In this paper we provide a first overview of spatiotemporal and gender distribution of citizen science workforce by analyzing 54 million classifications contributed by more than 340 thousand citizen science volunteers from 198 countries to one of the largest online citizen science platforms, Zooniverse. First we report on the uneven geographical distribution of the citizen scientist and model the variations among countries based on the socio-economic conditions as well as the level of research investment in each country. Analyzing the temporal features of contributions, we report on high “burstiness” of participation instances as well as the leisurely nature of participation suggested by the time of the day that the citizen scientists were the most active. Finally, we discuss the gender imbalance among online citizen scientists (about 30% female) and compare it with other collaborative projects as well as the gender distribution in more formal scientific activities. Online citizen science projects need further attention from outside of the academic community, and our findings can help attract the attention of public and private stakeholders, as well as to inform the design of the platforms and science policy making processes.
91Scopus© Citations 9
- PublicationSelling sex: what determines rates and popularity? An analysis of 11,500 online profilesSex work, or the exchange of sexual services for money or goods, is ubiquitous across eras and cultures. However, the practice of selling sex is often hidden due to stigma and the varying legal status of sex work. Online platforms that sex workers use to advertise services have become an increasingly important means of studying a market that is largely hidden. Although prior literature has primarily shed light on sex work from a public health or policy perspective (focusing largely on female sex workers), there are few studies that empirically research patterns of service provision in online sex work. This study investigated the determinants of pricing and popularity in the market for commercial sexual services online by using data from the largest UK network of online sexual services, a platform that is the industry-standard for sex workers. While the size of these influences varies across genders, nationality, age and the services provided are shown to be primary drivers of rates and popularity in sex work.
232Scopus© Citations 3
- PublicationPositive algorithmic bias cannot stop fragmentation in homophilic networksFragmentation, echo chambers, and their amelioration in social networks have been a growing concern in the academic and non-academic world. This paper shows how, under the assumption of homophily, echo chambers and fragmentation are system-immanent phenomena of highly flexible social networks, even under ideal conditions for heterogeneity. We achieve this by finding an analytical, network-based solution to the Schelling model and by proving that weak ties do not hinder the process. Furthermore, we derive that no level of positive algorithmic bias in the form of rewiring is capable of preventing fragmentation and its effect on reducing the fragmentation speed is negligible.
Scopus© Citations 8 189
- PublicationControversy around climate change reports: a case study of Twitter responses to the 2019 IPCC report on landIn August 2019, the Intergovernmental Panel on Climate Change (IPCC) published its Special Report on Climate Change and Land (SRCCL), which generated extensive societal debate and interest in mainstream and social media. Using computational and conceptual text analysis, we examined more than 6,000 English-language posts on Twitter to establish the relative presence of different topics. Then, we assessed their levels of toxicity and sentiment polarity as an indication of contention and controversy. We find first that meat consumption and dietary options became one of the most discussed issues on Twitter in response to the IPCC report, even though it was a relatively minor element of the report; second, this new issue of controversy (meat and diet) had similar, high levels of toxicity to strongly contentious issues in previous IPCC reports (skepticism about climate science and the credibility of the IPCC). We suggest that this is in part a reflection of increasingly polarized narratives about meat and diet found in other areas of public discussion and of a movement away from criticism of climate science towards criticism of climate solutions. Finally, we discuss the possible implications of these findings for the work of the IPCC in anticipating responses to its reports and responding to them effectively.
Scopus© Citations 18 169
- PublicationThe Kaleidoscope of Privacy: Differences across French, German, UK, and US GDPR Media DiscourseConceptions of privacy differ by culture. In the Internet age, digital tools continuously challenge the way users, technologists, and governments define, value, and protect privacy. National and supranational entities attempt to regulate privacy and protect data managed online. The European Union passed the General Data Protection Regulation (GDPR), which took effect on 25 May 2018. The research presented here draws on two years of media reporting on GDPR from French, German, UK, and US sources. We use the unsupervised machine learning method of topic modelling to compare the thematic structure of the news articles across time and geographic regions. Our work emphasises the relevance of regional differences regarding valuations of privacy and potential obstacles to the implementation of unilateral data protection regulation such as GDPR. We find that the topics and trends over time in GDPR media coverage of the four countries reflect the differences found across their traditional privacy cultures.
- PublicationCan the Wikipedia moderation model rescue the social marketplace of ideas?Facebook announced a community review program in December 2019 and Twitter launched a communitybased platform to address misinformation, called Birdwatch, in January 2021. We provide an overview of the potential affordances of such community based approaches to content moderation based on past research. While our analysis generally supports a community-based approach to content moderation, it also warns against potential pitfalls, particularly when the implementation of the new infrastructures does not promote diversity. We call for more multidisciplinary research utilizing methods from complex systems studies, behavioural sociology, and computational social science to advance the research on crowd-based content moderation.
- PublicationFootball is becoming more predictable; network analysis of 88 thousand matches in 11 major leaguesIn recent years, excessive monetization of football and professionalism among the players have been argued to have affected the quality of the match in different ways. On the one hand, playing football has become a high-income profession and the players are highly motivated; on the other hand, stronger teams have higher incomes and therefore afford better players leading to an even stronger appearance in tournaments that can make the game more imbalanced and hence predictable. To quantify and document this observation, in this work, we take a minimalist network science approach to measure the predictability of football over 26 years in major European leagues. We show that over time, the games in major leagues have indeed become more predictable. We provide further support for this observation by showing that inequality between teams has increased and the home-field advantage has been vanishing ubiquitously. We do not include any direct analysis on the effects of monetization on football’s predictability or therefore, lack of excitement; however, we propose several hypotheses which could be tested in future analyses.