A study on the friendship paradox – quantitative analysis and relationship with assortative mixing

The friendship paradox is the observation that friends of individuals tend to have more friends or be more popular than the individuals themselves. In this work, we first study local metrics to capture the strength of the paradox and the direction of the paradox from the perspective of individual nodes, i.e., an indication of whether the individual is more or less popular than its friends. These local metrics are aggregated, and global metrics are proposed to express the phenomenon on a network-wide level. Theoretical results show that the defined metrics are well-behaved enough to capture the friendship paradox. We also theoretically analyze the behavior of the friendship paradox for popular network models in order to understand regimes where friendship paradox occurs. These theoretical findings are complemented by experimental results on both network models and real-world networks. By conducting a correlation study between the proposed metrics and degree assortativity, we experimentally demonstrate that the phenomenon of the friendship paradox is related to the well-known phenomenon of assortative mixing

HIV non-B subtype distribution: emerging trends and risk factors for imported and local infections newly diagnosed in South Australia

Monitoring HIV subtype distribution is important for understanding transmission dynamics. Subtype B has historically been dominant in Australia, but in recent years new clades have appeared. Since 2000, clade data have been collected as part of HIV surveillance in South Australia. The aim of this study was to evaluate the prevalence of and risk factors for HIV-1 non-B subtypes. The study population was composed of newly diagnosed, genotyped HIV subjects in South Australia between 2000 and 2010. We analyzed time trends and subtype patterns in this cohort; notification data were aggregated into three time periods (2000–2003, 2004–2006, and 2007–2010). Main outcome measures were number of new non-B infections by year, exposure route, and other demographic characteristics. There were 513 new HIV diagnoses; 425 had information on subtype. The majority (262/425) were in men who have sex with men (MSM), predominantly subtype B and acquired in Australia. Infections acquired in Australia decreased from 77% (2000–2003) to 64% (2007–2010) ( p = 0.007) and correspondingly the proportion of subtype B declined from 85% to 68% ( p = 0.002). Non-B infections were predominantly (83%) heterosexual contacts, mostly acquired overseas (74%). The majority (68%) of non-B patients were born outside of Australia. There was a non-significant increase from 1.6% to 4.2% in the proportion of locally transmitted non-B cases (p = 0.3). Three non-B subtypes and two circulating recombinant forms (CRFs) were identified: CRF_AE (n = 41), C (n = 36), CRF_AG (n = 13), A (n = 9), and D (n = 2). There has been a substantial increase over the past decade in diagnosed non-B infections, primarily through cases acquired overseas

Studying Fake News via Network Analysis: Detection and Mitigation

Social media for news consumption is becoming increasingly popular due to its easy access, fast dissemination, and low cost. However, social media also enable the wide propagation of "fake news", i.e., news with intentionally false information. Fake news on social media poses significant negative societal effects, and also presents unique challenges. To tackle the challenges, many existing works exploit various features, from a network perspective, to detect and mitigate fake news. In essence, news dissemination ecosystem involves three dimensions on social media, i.e., a content dimension, a social dimension, and a temporal dimension. In this chapter, we will review network properties for studying fake news, introduce popular network types and how these networks can be used to detect and mitigation fake news on social media.Comment: Submitted as a invited book chapter in Lecture Notes in Social Networks, Springer Pres

Special Libraries, January 1932

Volume 23, Issue 1https://scholarworks.sjsu.edu/sla_sl_1932/1000/thumbnail.jp

Composition and Structure of a Large Online Social Network in the Netherlands

Limitations in data collection have long been an obstacle in research on friendship networks. Most earlier studies use either a sample of ego-networks, or complete network data on a relatively small group (e.g., a single organization). The rise of online social networking services such as Friendster and Facebook, however, provides researchers with opportunities to study friendship networks on a much larger scale. This study uses complete network data from Hyves, a popular online social networking service in the Netherlands, comprising over eight million members and over 400 million online friendship relations. In the first study of its kind for the Netherlands, I examine the structure of this network in terms of the degree distribution, characteristic path length, clustering, and degree assortativity. Results indicate that this network shares features of other large complex networks, but also deviates in other respects. In addition, a comparison with other online social networks shows that these networks show remarkable similarities

The contribution of the environment (especially diet) to breast cancer risk

Environmental factors play an important role in breast carcinogenesis. Opportunities for prevention are limited, however, because most of the known or suspected risk factors are not targets for modification. Dietary factors have generally not emerged as crucial contributors to mammary tumor causation. We still appear to be missing a critical piece of the breast cancer puzzle because we can only explain a moderate proportion of international and national variation in breast cancer rates. Research needs to pursue new avenues, focusing on exposure windows that have not yet been sufficiently explored, such as events between conception and adolescence, and on modifiable risk factors that show large variation within or between populations

Differences in risk factors for children with special health care needs (CSHCN) receiving needed specialty care by socioeconomic status

<p>Abstract</p> <p>Background</p> <p>The purpose of this study is to identify factors affecting CSHCN's receiving needed specialty care among different socioeconomic levels. Previous literature has shown that Socioeconomic Status (SES) is a significant factor in CHSHCN receiving access to healthcare. Other literature has shown that factors of insurance, family size, race/ethnicity and sex also have effects on these children's receipt of care. However, this literature does not address whether other factors such as maternal education, geographic location, age, insurance type, severity of condition, or race/ethnicity have different effects on receiving needed specialty care for children in each SES level.</p> <p>Methods</p> <p>Data were obtained from the National Survey of Children with Special Health Care Needs, 2000–2002. The study analyzed the survey which studies whether CHSCN who needed specialty care received it. The analysis included demographic characteristics, geographical location of household, severity of condition, and social factors. Multiple logistic regression models were constructed for SES levels defined by federal poverty level: < 199%; 200–299%; ≥ 300%.</p> <p>Results</p> <p>For the poorest children (,199% FPL) being uninsured had a strong negative effect on receiving all needed specialty care. Being Hispanic was a protective factor. Having more than one adult in the household had a positive impact on receipt of needed specialty care but a larger number of children in the family had a negative impact. For the middle income group of children (200–299% of FPL severity of condition had a strong negative association with receipt of needed specialty care.</p> <p>Children in highest income group (> 300% FPL) were positively impacted by living in the Midwest and were negatively impacted by the mother having only some college compared to a four-year degree.</p> <p>Conclusion</p> <p>Factors affecting CSHCN receiving all needed specialty care differed among socioeconomic groups. These differences should be addressed in policy and practice. Future research should explore the CSHCN population by income groups to better serve this population</p

Elevated level of inhibin-α subunit is pro-tumourigenic and pro-metastatic and associated with extracapsular spread in advanced prostate cancer

The biological function of inhibin-α subunit (INHα) in prostate cancer (PCa) is currently unclear. A recent study associated elevated levels of INHα in PCa patients with a higher risk of recurrence. This prompted us to use clinical specimens and functional studies to investigate the pro-tumourigenic and pro-metastatic function of INHα. We conducted a cross-sectional study to determine a link between INHα expression and a number of clinicopathological parameters including Gleason score, surgical margin, extracapsular spread, lymph node status and vascular endothelial growth factor receptor-3 expression, which are well-established prognostic factors of PCa. In addition, using two human PCa cell lines (LNCaP and PC3) representing androgen-dependent and -independent PCa respectively, we investigated the biological function of elevated levels of INHα in advanced cancer. Elevated expression of INHα in primary PCa tissues showed a higher risk of PCa patients being positive for clinicopathological parameters outlined above. Over-expressing INHα in LNCaP and PC3 cells demonstrated two different and cell-type-specific responses. INHα-positive LNCaP demonstrated reduced tumour growth whereas INHα-positive PC3 cells demonstrated increased tumour growth and metastasis through the process of lymphangiogenesis. This study is the first to demonstrate a pro-tumourigenic and pro-metastatic function for INHα associated with androgen-independent stage of metastatic prostate disease. Our results also suggest that INHα expression in the primary prostate tumour can be used as a predictive factor for prognosis of PCa