ResearchPad - social-networks https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Psychological risk indicators of disordered eating in athletes]]> https://www.researchpad.co/article/elastic_article_14546 This project examined risk factors of disordered eating in athletes by adapting and applying a theoretical model. It tested a previously proposed theoretical model and explored the utility of a newly formed model within an athletic population across gender, age, and sport type to explain disordered eating.DesignThe design was cross-sectional and the first phase in a series of longitudinal studies.Methods1,017 athletes completed online questionnaires related to social pressures, internalisation, body dissatisfaction, negative affect, restriction, and bulimia. Structural equation modelling was employed to analyse the fit of the measurement and structural models and to do invariance testing.ResultsThe original theoretical model failed to achieve acceptable goodness of fit (χ2 [70, 1017] = 1043.07; p < .0001. CFI = .55; GFI = .88; NFI = .53; RMSEA = .12 [90% CI = .111-.123]). Removal of non-significant pathways and addition of social media resulted in the model achieving a parsimonious goodness of fit (χ2 [19, 1017] = 77.58; p < .0001. CFI = .96; GFI = .98; NFI = .95; RMSEA = .055 [90% CI = .043-.068]). Invariance tests revealed that the newly revised model differed across gender, age, level, competition status, and length of sport participation.ConclusionThis study showed that the formation of disordered eating symptomology might not be associated with sport pressures experienced by athletes. It revealed that disordered eating development varies across gender, competition level, sport type, and age, which must be considered to prevent and treat disordered eating in athletes. ]]> <![CDATA[Left powerless: A qualitative social media content analysis of the Dutch #breakthesilence campaign on negative and traumatic experiences of labour and birth]]> https://www.researchpad.co/article/elastic_article_13813 Disrespect and abuse during labour and birth are increasingly reported all over the world. In 2016, a Dutch client organization initiated an online campaign, #genoeggezwegen (#breakthesilence) which encouraged women to share negative and traumatic maternity care experiences. This study aimed (1) to determine what types of disrespect and abuse were described in #genoeggezwegen and (2) to gain a more detailed understanding of these experiences.MethodsA qualitative social media content analysis was carried out in two phases. (1) A deductive coding procedure was carried out to identify types of disrespect and abuse, using Bohren et al.’s existing typology of mistreatment during childbirth. (2) A separate, inductive coding procedure was performed to gain further understanding of the data.Results438 #genoeggezwegen stories were included. Based on the typology of mistreatment during childbirth, it was found that situations of ineffective communication, loss of autonomy and lack of informed consent and confidentiality were most often described. The inductive analysis revealed five major themes: ‘‘lack of informed consent”; ‘‘not being taken seriously and not being listened to”; ‘‘lack of compassion”; ‘‘use of force”; and ‘‘short and long term consequences”. “Left powerless” was identified as an overarching theme that occurred throughout all five main themes.ConclusionThis study gives insight into the negative and traumatic maternity care experiences of Dutch women participating in the #genoeggezwegen campaign. This may indicate that disrespect and abuse during labour and birth do happen in the Netherlands, although the current study gives no insight into prevalence. The findings of this study may increase awareness amongst maternity care providers and the community of the existence of disrespect and abuse in Dutch maternity care, and encourage joint effort on improving care both individually and systemically/institutionally. ]]> <![CDATA["Clicks, likes, shares and comments" a systematic review of breast cancer screening discourse in social media]]> https://www.researchpad.co/article/N8d8d3073-6769-4a60-aed8-e2beb958c228

Background

Unsatisfactory participation rate at population based organised breast cancer screening is a long standing problem. Social media, with 3.2 billion users in 2019, is potentially an important site of breast cancer related discourse. Determining whether these platforms might be used as channels by screening providers to reach under-screened women may have considerable public health significance.

Objectives

By systematically reviewing original research studies on breast cancer related social media discourse, we had two aims: first, to assess the volume, participants and content of breast screening social media communication and second, to find out whether social media can be used by screening organisers as a channel of patient education.

Methods

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). After searching PubMed, ScienceDirect, Web of Science, Springer and Ebsco, 17 studies were found that met our criteria. A systematic narrative framework was used for data synthesis. Owing to the high degree of heterogeneity in social media channels, outcomes and measurement included in this study, a meta-analytic approach was not appropriate.

Results

The volume of breast cancer related social media discourse is considerable. The majority of participants are lay individuals as opposed to healthcare professionals or advocacy groups. The lay misunderstandings surrounding the harms and benefits of mammography is well mirrored in the content of social media discourse. Although there is criticism, breast cancer screening sentiment on the social media ranges from the neutral to the positive. Social media is suitable for offering peer emotional support for potential participants.

Conclusion

Dedicated breast screening websites operated by screening organisers would ensure much needed quality controlled information and also provide space for reliable question and answer forums, the sharing of personal experience and the provision of peer and professional support.

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<![CDATA[Mental health problems and social media exposure during COVID-19 outbreak]]> https://www.researchpad.co/article/Nb7fad802-34c4-4007-a6dc-8e780c86cbf8

Huge citizens expose to social media during a novel coronavirus disease (COVID-19) outbroke in Wuhan, China. We assess the prevalence of mental health problems and examine their association with social media exposure. A cross-sectional study among Chinese citizens aged≥18 years old was conducted during Jan 31 to Feb 2, 2020. Online survey was used to do rapid assessment. Total of 4872 participants from 31 provinces and autonomous regions were involved in the current study. Besides demographics and social media exposure (SME), depression was assessed by The Chinese version of WHO-Five Well-Being Index (WHO-5) and anxiety was assessed by Chinese version of generalized anxiety disorder scale (GAD-7). multivariable logistic regressions were used to identify associations between social media exposure with mental health problems after controlling for covariates. The prevalence of depression, anxiety and combination of depression and anxiety (CDA) was 48.3% (95%CI: 46.9%-49.7%), 22.6% (95%CI: 21.4%-23.8%) and 19.4% (95%CI: 18.3%-20.6%) during COVID-19 outbroke in Wuhan, China. More than 80% (95%CI:80.9%-83.1%) of participants reported frequently exposed to social media. After controlling for covariates, frequently SME was positively associated with high odds of anxiety (OR = 1.72, 95%CI: 1.31–2.26) and CDA (OR = 1.91, 95%CI: 1.52–2.41) compared with less SME. Our findings show there are high prevalence of mental health problems, which positively associated with frequently SME during the COVID-19 outbreak. These findings implicated the government need pay more attention to mental health problems, especially depression and anxiety among general population and combating with “infodemic” while combating during public health emergency.

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<![CDATA[Exponential random graph model parameter estimation for very large directed networks]]> https://www.researchpad.co/article/N437fb42a-ebf8-44aa-9399-d12b1354408e

Exponential random graph models (ERGMs) are widely used for modeling social networks observed at one point in time. However the computational difficulty of ERGM parameter estimation has limited the practical application of this class of models to relatively small networks, up to a few thousand nodes at most, with usually only a few hundred nodes or fewer. In the case of undirected networks, snowball sampling can be used to find ERGM parameter estimates of larger networks via network samples, and recently published improvements in ERGM network distribution sampling and ERGM estimation algorithms have allowed ERGM parameter estimates of undirected networks with over one hundred thousand nodes to be made. However the implementations of these algorithms to date have been limited in their scalability, and also restricted to undirected networks. Here we describe an implementation of the recently published Equilibrium Expectation (EE) algorithm for ERGM parameter estimation of large directed networks. We test it on some simulated networks, and demonstrate its application to an online social network with over 1.6 million nodes.

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<![CDATA[Loneliness, Social Integration, and Incident Dementia Over 6 Years: Prospective Findings From the English Longitudinal Study of Ageing]]> https://www.researchpad.co/article/Nbf862093-47a8-4b95-acba-1356f25bbc70

Abstract

Objectives

Social relationships are important for the maintenance of cognitive function at older ages, with both objective features of social networks and perceived social connections (loneliness) being relevant. There is limited evidence about how different aspects of social experience predict diagnosed dementia.

Methods

The sample comprised 6,677 dementia-free individuals at baseline (2004) from the English Longitudinal Study of Ageing. Baseline information on loneliness, number of close relationships, marital status, and social isolation (contact with family and friends and participation in organizations) was analyzed in relation to incident dementia over an average 6.25 years using Cox regression, controlling for potential confounding factors.

Results

Two hundred twenty participants developed dementia during follow-up. In multivariable analyses, dementia risk was positively related to greater loneliness (hazard ratio 1.40, 95% confidence interval 1.09–1.80, p = .008), and inversely associated with number of close relationships (p < .001) and being married (p = .018). Sensitivity analyses testing for reverse causality and different criteria for diagnosing dementia confirmed the robustness of these findings. There was no association with social isolation.

Discussion

Dementia risk is associated with loneliness and having fewer close relationships in later life. The underlying mechanisms remain to be elucidated, but efforts to enhance older peoples’ relationship quality may be relevant to dementia risk.

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<![CDATA[Age and Gender Differences in Social Network Composition and Social Support Among Older Rural South Africans: Findings From the HAALSI Study]]> https://www.researchpad.co/article/N6024b835-113c-4d32-b5f8-7fa4a5971143

Abstract

Objectives

Drawing on the “Health and Aging in Africa: A Longitudinal Study of an INDEPTH community in South Africa” (HAALSI) baseline survey, we present data on older adults’ social networks and receipt of social support in rural South Africa. We examine how age and gender differences in social network characteristics matched with patterns predicted by theories of choice- and constraint-based network contraction in older adults.

Method

We used regression analysis on data for 5,059 South African adults aged 40 and older.

Results

Older respondents reported fewer important social contacts and less frequent communication than their middle-aged peers, largely due to fewer nonkin connections. Network size difference between older and younger respondents was greater for women than for men. These gender and age differences were explicable by much higher levels of widowhood among older women compared to younger women and older men. There was no evidence for employment-related network contraction or selective retention of emotionally supportive ties.

Discussion

Marriage-related structural constraints impacted on older women’s social networks in rural South Africa, but did not explain choice-based network contraction. These findings suggest that many older women in rural Africa, a growing population, may have an unmet need for social support.

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<![CDATA[CHATTIER WITH FRIENDS: OLDER ADULTS’ DAILY SOCIAL CONTACT AND CONVERSATION]]> https://www.researchpad.co/article/Nad3a7125-b5a8-42d9-baee-d5e7839798ab

Abstract

Studies suggest conversation improves cognitive skills among older adults. While contact with family members is common in late life, contact with friends and acquaintances is relatively less frequent. Yet, we know little about how often older adults engage in conversation when they have contact with different social partners. This study used data from the Daily Experiences and Well-being Study to investigate how older adults talk with different social partners on a daily basis. Participants (N = 303) completed an initial interview about their social partners and reported on their contact with each social partner in ecological momentary assessments every 3 hours across 5 to 6 days. Participants also wore Electronically Activated Recorders (EAR), which captured snippets of their daily conversation. Findings revealed that contact with family members (e.g., spouse, children, siblings) occurred most often, with less frequent contact with other social partners (e.g., acquaintances, neighbors), and then friends. Multilevel models also revealed that participants talked more (i.e., saying more words in each 30-second snippet and had a greater proportion of snippets when they talked) when they had contact with their friends than when they had contact with family members or other social partners. Results from these multiple methods suggest that daily contact with friends could potentially encourage conversation that may facilitate cognitive functioning among older adults.

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<![CDATA[Algorithmic bias amplifies opinion fragmentation and polarization: A bounded confidence model]]> https://www.researchpad.co/article/5c8823d7d5eed0c484639133

The flow of information reaching us via the online media platforms is optimized not by the information content or relevance but by popularity and proximity to the target. This is typically performed in order to maximise platform usage. As a side effect, this introduces an algorithmic bias that is believed to enhance fragmentation and polarization of the societal debate. To study this phenomenon, we modify the well-known continuous opinion dynamics model of bounded confidence in order to account for the algorithmic bias and investigate its consequences. In the simplest version of the original model the pairs of discussion participants are chosen at random and their opinions get closer to each other if they are within a fixed tolerance level. We modify the selection rule of the discussion partners: there is an enhanced probability to choose individuals whose opinions are already close to each other, thus mimicking the behavior of online media which suggest interaction with similar peers. As a result we observe: a) an increased tendency towards opinion fragmentation, which emerges also in conditions where the original model would predict consensus, b) increased polarisation of opinions and c) a dramatic slowing down of the speed at which the convergence at the asymptotic state is reached, which makes the system highly unstable. Fragmentation and polarization are augmented by a fragmented initial population.

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<![CDATA[Matching response to need: What makes social networks fit for providing bereavement support?]]> https://www.researchpad.co/article/5c8accc6d5eed0c48498ff77

The objectives of this study were to explore the goodness of fit between the bereaved peoples’ needs and the support offered by their social networks; to ascertain whether this support was experienced as helpful or unhelpful by bereaved people; and to explore both the types of social networks that offer effective support and the characteristics of the communities that encourage and nurture such networks. This study was based on qualitative interviews from twenty bereaved people, in Western Australia, interviewed in 2013. A framework analysis of these interviews was undertaken using a deductive approach based on the goodness of fit framework. Much of this support is provided informally in community settings by a range of people already involved in the everyday lives of those recently bereaved; and that support can be helpful or unhelpful depending on its amount, timing, function and structure. Improving the fit between the bereaved person’s needs and the support offered may thus involve identifying and enhancing the caring capacity of existing networks. An important strategy for achieving this is to train community members in mapping and developing these naturally occurring networks. Some such networks will include relationships of long standing, others may be circles of care formed during a period of caring. Peer support bereavement networks develop from these existing networks and may also recruit new members who were not part of the caring circle. The findings endorse social models of bereavement care that fit within a public health approach rather than relying solely on professional care. As exemplified by Compassionate Communities policies and practices, establishing collaboration between community networks and professional services is vital for effective and sustainable bereavement care.

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<![CDATA[Description of network meta-analysis geometry: A metrics design study]]> https://www.researchpad.co/article/5c76fe29d5eed0c484e5b60f

Background

The conduction and report of network meta-analysis (NMA), including the presentation of the network-plot, should be transparent. We aimed to propose metrics adapted from graph theory and social network-analysis literature to numerically describe NMA geometry.

Methods

A previous systematic review of NMAs of pharmacological interventions was performed. Data on the graph’s presentation were collected. Network-plots were reproduced using Gephi 0.9.1. Eleven geometric metrics were tested. The Spearman test for non-parametric correlation analyses and the Bland-Altman and Lin’s Concordance tests were performed (IBM SPSS Statistics 24.0).

Results

From the 477 identified NMAs only 167 graphs could be reproduced because they provided enough information on the plot characteristics. The median nodes and edges were 8 (IQR 6–11) and 10 (IQR 6–16), respectively, with 22 included studies (IQR 13–35). Metrics such as density (median 0.39, ranged 0.07–1.00), median thickness (2.0, IQR 1.0–3.0), percentages of common comparators (median 68%), and strong edges (median 53%) were found to contribute to the description of NMA geometry. Mean thickness, average weighted degree and average path length produced similar results than other metrics, but they can lead to misleading conclusions.

Conclusions

We suggest the incorporation of seven simple metrics to report NMA geometry. Editors and peer-reviews should ensure that guidelines for NMA report are strictly followed before publication.

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<![CDATA[Soil health pilot study in England: Outcomes from an on-farm earthworm survey]]> https://www.researchpad.co/article/5c76fe56d5eed0c484e5b8f1

Earthworms are primary candidates for national soil health monitoring as they are ecosystem engineers that benefit both food production and ecosystem services associated with soil security. Supporting farmers to monitor soil health could help to achieve the policy aspiration of sustainable soils by 2030 in England; however, little is known about how to overcome participation barriers, appropriate methodologies (practical, cost-effective, usefulness) or training needs. This paper presents the results from a pilot #60minworms study which mobilised farmers to assess over >1300 ha farmland soils in spring 2018. The results interpretation framework is based on the presence of earthworms from each of the three ecological groups at each observation (20 x 20 cm x 20 cm pit) and spatially across a field (10 soil pits). Results showed that most fields have basic earthworm presence and abundance, but 42% fields may be over-worked as indicated by absence/rarity of epigeic and/or anecic earthworms. Tillage had a negative impact (p < 0.05) on earthworm populations and organic matter management did not mitigate tillage impacts. In terms of farmer participation, Twitter and Farmers Weekly magazine were highly effective channels for recruitment. Direct feedback from participants included excellent scores in trust, value and satisfaction of the protocol (e.g. 100% would do the test again) and 57% would use their worm survey results to change their soil management practices. A key training need in terms of earthworm identification skills was reported. The trade-off between data quality, participation rates and fieldwork costs suggests there is potential to streamline the protocol further to #30minworms (5 pits), incurring farmer fieldwork costs of approximately £1.48 ha-1. At national scales, £14 million pounds across 4.7 M ha-1 in fieldwork costs per survey could be saved by farmer participation.

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<![CDATA[Social media usage patterns during natural hazards]]> https://www.researchpad.co/article/5c6dc99cd5eed0c484529ecf

Natural hazards are becoming increasingly expensive as climate change and development are exposing communities to greater risks. Preparation and recovery are critical for climate change resilience, and social media are being used more and more to communicate before, during, and after disasters. While there is a growing body of research aimed at understanding how people use social media surrounding disaster events, most existing work has focused on a single disaster case study. In the present study, we analyze five of the costliest disasters in the last decade in the United States (Hurricanes Irene and Sandy, two sets of tornado outbreaks, and flooding in Louisiana) through the lens of Twitter. In particular, we explore the frequency of both generic and specific food-security related terms, and quantify the relationship between network size and Twitter activity during disasters. We find differences in tweet volume for keywords depending on disaster type, with people using Twitter more frequently in preparation for Hurricanes, and for real-time or recovery information for tornado and flooding events. Further, we find that people share a host of general disaster and specific preparation and recovery terms during these events. Finally, we find that among all account types, individuals with “average” sized networks are most likely to share information during these disasters, and in most cases, do so more frequently than normal. This suggests that around disasters, an ideal form of social contagion is being engaged in which average people rather than outsized influentials are key to communication. These results provide important context for the type of disaster information and target audiences that may be most useful for disaster communication during varying extreme events.

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<![CDATA[Perceptions of cervical cancer prevention on Twitter uncovered by different sampling strategies]]> https://www.researchpad.co/article/5c6b269dd5eed0c484289d78

Introduction

Cervical cancer prevention is possible through use of the HPV vaccine and Pap tests, yet the vaccine remains underutilized.

Methods

We obtained publicly-available Twitter data from 2014 using three sampling strategies (top-ranked, simple random sample, and topic model) based on key words related to cervical cancer prevention. We conducted a content analysis of 100 tweets from each of the three samples and examined the extent to which the narratives and frequency of themes differed across samples.

Results

Advocacy-related tweets constituted the most prevalent theme to emerge across all three sample types, and were most frequently found in the top-ranked sample. A random sample detected the same themes as topic modeling, but the relative frequency of themes identified from topic modeling fell in-between top-ranked and random samples.

Discussion

Variations in themes uncovered by different sampling methods suggest it is useful to qualitatively assess the relative frequency of themes to better understand the breadth and depth of social media conversations about health.

Conclusions

Future studies using social media data should consider sampling methods to uncover a wider breadth of conversations about health on social media.

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<![CDATA[Examining individual and geographic factors associated with social isolation and loneliness using Canadian Longitudinal Study on Aging (CLSA) data]]> https://www.researchpad.co/article/5c5df369d5eed0c484581267

Background

A large body of research shows that social isolation and loneliness have detrimental health consequences. Identifying individuals at risk of social isolation or loneliness is, therefore, important. The objective of this study was to examine personal (e.g., sex, income) and geographic (rural/urban and sociodemographic) factors and their association with social isolation and loneliness in a national sample of Canadians aged 45 to 85 years.

Methods

The study involved cross-sectional analyses of baseline data from the Canadian Longitudinal Study on Aging that were linked to 2016 census data at the Forward Sortation Area (FSA) level. Multilevel logistic regression analyses were conducted to examine the association between personal factors and geographic factors and social isolation and loneliness for the total sample, and women and men, respectively.

Results

The prevalence of social isolation and loneliness was 5.1% and 10.2%, respectively, but varied substantially across personal characteristics. Personal characteristics (age, sex, education, income, functional impairment, chronic diseases) were significantly related to both social isolation and loneliness, although some differences emerged in the direction of the relationships for the two measures. Associations also differed somewhat for women versus men. Associations between some geographic factors emerged for social isolation, but not loneliness. Living in an urban core was related to increased odds of social isolation, an effect that was no longer significant when FSA-level factors were controlled for. FSAs with a higher percentage of 65+ year old residents with low income were consistently associated with higher odds of social isolation.

Conclusion

The findings indicate that socially isolated individuals are, to some extent, clustered into areas with a high proportion of low-income older adults, suggesting that support and resources could be targeted at these areas. For loneliness, the focus may be less on where people live, but rather on personal characteristics that place individuals at risk.

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<![CDATA[Physical co-presence intensity: Measuring dynamic face-to-face interaction potential in public space using social media check-in records]]> https://www.researchpad.co/article/5c6b26b0d5eed0c484289ea4

Urban public spaces facilitate social interactions between people, reflecting the shifting functionality of spaces. There is no commonly-held consensus on the quantification methods for the dynamic interplay between spatial geometry, urban movement, and face-to-face encounters. Using anonymized social media check-in records from Shanghai, China, this study proposes pipelines for quantifying physical face-to-face encounter potential patterns through public space networks between local and non-local residents sensed by social media over time from space to space, in which social difference, cognitive cost, and time remoteness are integrated as the physical co-presence intensity index. This illustrates the spatiotemporally different ways in which the built environment binds various groups of space users configurationally via urban streets. The variation in face-to-face interaction patterns captures the fine-resolution patterns of urban flows and a new definition of street hierarchy, illustrating how urban public space systems deliver physical meeting opportunities and shape the spatial rhythms of human behavior from the public to the private. The shifting encounter potentials through streets are recognized as reflections of urban centrality structures with social interactions that are spatiotemporally varying, projected in the configurations of urban forms and functions. The results indicate that the occurrence probability of face-to-face encounters is more geometrically scaled than predicted based on the co-location probability of two people using metric distance alone. By adding temporal and social dimensions to urban morphology studies, and the field of space syntax research in particular, we suggest a new approach of analyzing the temporal urban centrality structures of the physical interaction potentials based on trajectory data, which is sensitive to the transformation of the spatial grid. It sheds light on how to adopt urban design as a social instrument to facilitate the dynamically changing social interaction potential in the new data environment, thereby enhancing spatial functionality and the social well-being.

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<![CDATA[Cultural transmission modes of music sampling traditions remain stable despite delocalization in the digital age]]> https://www.researchpad.co/article/5c633933d5eed0c484ae6217

Music sampling is a common practice among hip-hop and electronic producers that has played a critical role in the development of particular subgenres. Artists preferentially sample drum breaks, and previous studies have suggested that these may be culturally transmitted. With the advent of digital sampling technologies and social media the modes of cultural transmission may have shifted, and music communities may have become decoupled from geography. The aim of the current study was to determine whether drum breaks are culturally transmitted through musical collaboration networks, and to identify the factors driving the evolution of these networks. Using network-based diffusion analysis we found strong evidence for the cultural transmission of drum breaks via collaboration between artists, and identified several demographic variables that bias transmission. Additionally, using network evolution methods we found evidence that the structure of the collaboration network is no longer biased by geographic proximity after the year 2000, and that gender disparity has relaxed over the same period. Despite the delocalization of communities by the internet, collaboration remains a key transmission mode of music sampling traditions. The results of this study provide valuable insight into how demographic biases shape cultural transmission in complex networks, and how the evolution of these networks has shifted in the digital age.

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<![CDATA[Correlated impulses: Using Facebook interests to improve predictions of crime rates in urban areas]]> https://www.researchpad.co/article/5c61e910d5eed0c48496f765

Much research has examined how crime rates vary across urban neighborhoods, focusing particularly on community-level demographic and social characteristics. A parallel line of work has treated crime at the individual level as an expression of certain behavioral patterns (e.g., impulsivity). Little work has considered, however, whether the prevalence of such behavioral patterns in a neighborhood might be predictive of local crime, in large part because such measures are hard to come by and often subjective. The Facebook Advertising API offers a special opportunity to examine this question as it provides an extensive list of “interests” that can be tabulated at various geographic scales. Here we conduct an analysis of the association between the prevalence of interests among the Facebook population of a ZIP code and the local rate of assaults, burglaries, and robberies across 9 highly populated cities in the US. We fit various regression models to predict crime rates as a function of the Facebook and census demographic variables. In general, models using the variables for the interests of the whole adult population on Facebook perform better than those using data on specific demographic groups (such as Males 18-34). In terms of predictive performance, models combining Facebook data with demographic data generally have lower error rates than models using only demographic data. We find that interests associated with media consumption and mating competition are predictive of crime rates above and beyond demographic factors. We discuss how this might integrate with existing criminological theory.

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<![CDATA[PopRank: Ranking pages’ impact and users’ engagement on Facebook]]> https://www.researchpad.co/article/5c58d664d5eed0c484031d68

The advent of social networks revolutionized the way people access to information sources. Understanding the complex relationship between these sources and users is crucial. We introduce an algorithm, that we call PopRank, to assess both the Impact of Facebook pages as well as users’ Engagement on the basis of their mutual interactions. The ideas behind the PopRank are that i) high impact pages attract many users with a low engagement, which means that they receive comments from users that rarely comment, and ii) high engagement users interact with high impact pages, that is they mostly comment pages with a high popularity. The resulting ranking of pages can predict the number of comments a page will receive and the number of its future posts. Pages’ impact turns out to be slightly dependent on the quality of pages’ informative content (e.g., science vs conspiracy) but independent of users’ polarization.

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<![CDATA[Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study]]> https://www.researchpad.co/article/5c6448e7d5eed0c484c2f17d

A recurrent criticism concerning the use of online social media data in political science research is the lack of demographic information about social media users. By employing a face-recognition algorithm to the profile pictures of Facebook users, the paper derives two fundamental demographic characteristics (age and gender) of a sample of Facebook users who interacted with the most relevant British parties in the two weeks before the Brexit referendum of 23 June 2016. The article achieves the goals of (i) testing the precision of the algorithm, (ii) testing its validity, (iii) inferring new evidence on digital mobilisation, and (iv) tracing the path for future developments and application of the algorithm. The findings show that the algorithm is reliable and that it can be fruitfully used in political and social sciences both to confirm the validity of survey data and to obtain information from populations that are generally unavailable within traditional surveys.

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