scholarly journals Unravelling the Social Network of COVID-19 in India from 30 January to 6 April 2020

2020 ◽  
Author(s):  
Sarita Azad ◽  
Sushma Devi
Keyword(s):  
Social Network ◽  
National Level ◽  
Eigenvector Centrality ◽  
Indian States ◽  
Important Conclusion ◽  
The Social ◽  
Community Transmission ◽  
Influential Node ◽  
Network Metrics ◽  
Local Transmission

Social network analysis is an essential means to uncover and examine infectious contact relations between individuals. This paper aims to investigate the spread of coronavirus disease (COVID-19) from international to the national level and find a few super spreaders which played a central role in the transmission of disease in India. Our network metrics calculated from 30 January to 6 April 2020 revealed that the maximum numbers of connections were established from Dubai (degree-144) and UK (degree-64). These two countries played a crucial role in diffusing the disease in Indian states. The eigenvector centrality of Dubai is found to be the highest, and this marked it the most influential node. However, based on the modularity class, we found that the different clusters were formed across Indian states which demonstrated the forming of a multi-layered social network structure.A significant increase in the confirmed cases was reported during the first lockdown 1.0 (22 March 2020) primarily attributed to a gathering in Delhi Religious Conference (DRC) known as Tabliqui Jamaat. As of 6 April 2020, the overall structure of the network has encompassed local transmission, and it was significantly seen in the states like Gujarat, Rajasthan, and Karnataka. An important conclusion drawn from the presented social network reveals that the COVID-19 spread till 6 April was mainly due to the local transmission across Indian states. The timely quarantine of infected cases in DRC has not led it to spread at the level of community transmission.

scholarly journals Tracking the spread of COVID-19 in India via social networks in the early phase of the pandemic

2020 ◽  
Vol 27 (8) ◽  
Author(s):  
Sarita Azad ◽  
Sushma Devi
Keyword(s):  
Tamil Nadu ◽  
National Level ◽  
International Travel ◽  
Primary Data ◽  
Eigenvector Centrality ◽  
Indian States ◽  
Social Network Structure ◽  
History Of ◽  
Influential Node ◽  
The Uk

Abstract Background The coronavirus pandemic (COVID-19) has spread worldwide via international travel. This study traced its diffusion from the global to national level and identified a few superspreaders that played a central role in the transmission of this disease in India. Data and methods We used the travel history of infected patients from 30 January to 6 April 6 2020 as the primary data source. A total of 1386 cases were assessed, of which 373 were international and 1013 were national contacts. The networks were generated in Gephi software (version 0.9.2). Results The maximum numbers of connections were established from Dubai (degree 144) and the UK (degree 64). Dubai’s eigenvector centrality was the highest that made it the most influential node. The statistical metrics calculated from the data revealed that Dubai and the UK played a crucial role in spreading the disease in Indian states and were the primary sources of COVID-19 importations into India. Based on the modularity class, different clusters were shown to form across Indian states, which demonstrated the formation of a multi-layered social network structure. A significant increase in confirmed cases was reported in states like Tamil Nadu, Delhi and Andhra Pradesh during the first phase of the nationwide lockdown, which spanned from 25 March to 14 April 2020. This was primarily attributed to a gathering at the Delhi Religious Conference known as Tabliqui Jamaat. Conclusions COVID-19 got induced into Indian states mainly due to International travels with the very first patient travelling from Wuhan, China. Subsequently, the contacts of positive cases were located, and a significant spread was identified in states like Gujarat, Rajasthan, Maharashtra, Kerala and Karnataka. The COVID-19’s spread in phase one was traced using the travelling history of the patients, and it was found that most of the transmissions were local.

Social Networks and Social Complexity in Female-bonded Primates

2010 ◽  
Author(s):  
Julia Lehmann ◽  
Katherine Andrews ◽  
Robin Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Social Complexity ◽  
Social Bonds ◽  
Primate Brain ◽  
The Social ◽  
Group Members ◽  
Primate Group ◽  
Network Metrics ◽  
The Relationship

Most primates are intensely social and spend a large amount of time servicing social relationships. The social brain hypothesis suggests that the evolution of the primate brain has been driven by the necessity of dealing with increased social complexity. This chapter uses social network analysis to analyse the relationship between primate group size, neocortex ratio and several social network metrics. Findings suggest that social complexity may derive from managing indirect social relationships, i.e. relationships in which a female is not directly involved, which may pose high cognitive demands on primates. The discussion notes that a large neocortex allows individuals to form intense social bonds with some group members while at the same time enabling them to manage and monitor less intense indirect relationships without frequent direct involvement with each individual of the social group.

scholarly journals Football Team Social Structure and Perceived Support for Reporting Concussion Symptoms: Insights from a Social Network Analysis

2019 ◽  
Vol 24 (6) ◽  
pp. 256-262
Author(s):  
Heidi A. Wayment ◽  
Ann H. Huffman ◽  
Monica Lininger ◽  
Patrick C. Doyle
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Influence ◽  
Perceived Support ◽  
Social Connections ◽  
Eigenvector Centrality ◽  
Football Team ◽  
The Social ◽  
Important Others

Social network analysis (SNA) is a uniquely situated methodology to examine the social connections between players on a team, and how team structure may be related to self-reported team cohesion and perceived support for reporting concussion symptoms. Team belonging was positively associated with number of friendship ties (degree; r = .23, p < .05), intermediate ties between teammates (betweenness; r = .21, p < .05), and support from both teammates (r = .21, p < .05) and important others (r = .21, p < .05) for reporting concussion symptoms. Additionally, an SNA-derived measure of social influence, eigenvector centrality, was associated with football identity (r = .34, p < .01), and less support from important others (r = –.24, p < .05) regarding symptom reporting. Discussion focuses on why consideration of social influence dynamics may help improve concussion-related education efforts.

The superhuman being manipulated: the digital and the real personality on social networks

2019 ◽  
Vol 25242644 ◽  
pp. 19-25
Author(s):  
Denys Ivanov
Keyword(s):  
Social Network ◽  
Data Collection ◽  
National Level ◽  
High Data ◽  
The Social ◽  
The Usa ◽  
Processing Information ◽  
Using Data ◽  
Democratic Elections ◽  
Global Data

The main objective of the article is to describe the basics of using data on the activity/passivity of social network users and gadget owners, as well as related challenges. Using the method of content analysis, we consider the profile in the social network as the profile of the identity of the owner. Through the prism of presence/absence of information, we can assume who is this or that user. Based on various criteria, we can determine to which category a particular user can be attributed. We consider the profile in the network as a place of confession for the user, and the gadget considered as “prosthesis” that everyone needs to achieve their goals. Therefore, the person and the gadget are considered holistic. We provide information on the development of the OCEAN method, which allows us to «measure» the human psyche based on auto-expression on a social network. We present examples of using users data by Cambridge Analytics for political purposes, such as the 2016 presidential election in the USA, Brexit, and examples showing global data collection, high data representativeness, automating data collection processes, processing information from social network users and their profiling. To demonstrate the level of representativeness of the data, we compared the number of Facebook users in the USA with a population of this country. For comparison purpose, we also analyzed the statistics of users of the Android system. Based on the methods of induction and deduction, as a result, we presented the problems associated with the use of information of gadgets owners (identity theft, using data for manipulation (political and consumer) purpose, threats to democratic elections and the loss of subjectivity in the decision-making process). We also noted the trend (disappointment of people who understand the situation in the political system as a whole), which will develop as a reaction to these processes. As a conclusion, we propose solutions that can reduce negative processes (improving legislation at the international and national level, promoting awareness). The significance of this study for science and society is to clarify the problems associated with big data, which often remain outside the scope of discussion.

scholarly journals Network connections, dyadic bonds and fitness in wild female baboons

2016 ◽  
Vol 3 (7) ◽  
pp. 160255 ◽  
Author(s):  
Dorothy L. Cheney ◽  
Joan B. Silk ◽  
Robert M. Seyfarth
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Offspring Survival ◽  
Eigenvector Centrality ◽  
Wild Female ◽  
Adaptive Value ◽  
The Social ◽  
Social Partners ◽  
Fitness Benefits ◽  
Wild Baboons

In many social mammals, females who form close, differentiated bonds with others experience greater offspring survival and longevity. We still know little, however, about how females' relationships are structured within the social group, or whether connections beyond the level of the dyad have any adaptive value. Here, we apply social network analysis to wild baboons in order to evaluate the comparative benefits of dyadic bonds against several network measures. Results suggest that females with strong dyadic bonds also showed high eigenvector centrality, a measure of the extent to which an individual's partners are connected to others in the network. Eigenvector centrality was a better predictor of offspring survival than dyadic bond strength. Previous results have shown that female baboons derive significant fitness benefits from forming close, stable bonds with several other females. Results presented here suggest that these benefits may be further augmented if a female's social partners are themselves well connected to others within the group rather than being restricted to a smaller clique.

scholarly journals Analysis of Social Phenomenon on Tattoo Using Big Data and Social Network Analysis - News texts for the last year as collated -

2021 ◽  
Vol 27 (5) ◽  
pp. 1139-1145
Author(s):  
Ran-Sug Seo
Keyword(s):  
Big Data ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Academic Research ◽  
Eigenvector Centrality ◽  
Social Phenomena ◽  
The Past ◽  
The Social ◽  
Newspaper Articles

The purpose of this study was to identify the social phenomena of tattoo, which have been of constant interest in our society, through analysis of social networks collected from big data on what the social phenomena implied in keywords emphasized in newspaper articles over the past year. To this end, by analyzing keywords about tattoos that frequently appeared in newspaper articles, we could see what the main interests of social phenomena related to tattoos were. Data on tattoos were collected from newspaper articles over the past year and analyzed how they formed meaning regarding the relationship structure and centrality between the keywords at issue through social network analysis. These findings provide basic data on social discussions and policy directions related to tattoos in practice and discussions related to ways to improve them. This study is an extension from existing quantitative research by analyzing the social phenomena of tattoos through Bigdata and social network analysis. Apart from statistical surveys or subjective qualitative research, we have approached them with content analysis using big data and social network analysis. The conclusion of this study is as follows. First, as a result of analyzing the word cloud regarding tattoos, it was confirmed that “rose” and “300” were the most prominent, and there were keywords that could analyze various other social phenomena. Second, as a result of analysis by connection centrality, it was proved that the social interest and popularity of tattoos increased. Third, as a result of analysis by eigenvector centrality, the popularity of tattoos was proved. It objectified academic research by attempting research from a different perspective from the analysis of research trends and provided visualized research results of readers.

scholarly journals El análisis de redes sociales como instrumento del Trabajo Social frente a la COVID 19

2021 ◽  
pp. 35
Author(s):  
Joaquín Castillo de Mesa
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Interactions ◽  
Redes Sociales ◽  
Infected People ◽  
Social Nature ◽  
The Social ◽  
Community Transmission ◽  
Trabajo Social

El consenso científico señala que la mejor manera de frenar la propagación de la COVID-19 es mediante el rastreo de los contactos de las personas infectadas. Esta medida tiene carácter social, ya que busca analizar las redes de las personas para detectar de forma temprana quiénes están en riesgo de haber sido infectados, alertarles e imponerles la cuarentena, una medida de aislamiento social que impida la potencial propagación.  Hasta el momento mucho se ha hablado sobre qué profesionales deben realizar este rastreo pero poco acerca de cómo se debe realizar este rastreo. En este artículo, en primer lugar, se define qué es el rastreo, qué profesionales están más preparados para estas tareas y cómo se está llevando a cabo en España, encontrando ciertas carencias en cuanto al uso de metodologías científicas que apoyen la labor de rastreo. A partir de la literatura científica que analiza cómo afecta la socialización a la propagación se desarrolla una simulación sobre cómo se puede propagar la COVID 19 durante las interacciones sociales de las personas en sus distintos ámbitos de socialización. Sobre esta simulación se utiliza análisis de redes sociales y determinados algoritmos de detección de comunidades y de análisis de cohesión, para mostrar la idoneidad de estas metodologías para que el rastreo. Los resultados muestran que con el apoyo del análisis de redes sociales y de determinados algoritmos se accede de forma precoz a información clave sobre comunidades formadas en la estructura de red y sobre quiénes son los superpropagadores y los intermediadores entre las comunidades detectadas. Esto puede ayudar a priorizar la puesta en contacto con estas personas para cortar las cadenas de trasmisión comunitaria. Finalmente discutimos acerca de la idoneidad de que los profesionales del Trabajo Social se capaciten en estas metodologías para poder desarrollar esta labor del rastreo.Scientific consensus indicates that the best way to slow the spread of COVID 19 is by tracing the contacts of infected people. This measure has a social nature, since it seeks to analyze people’s networks to detect early who is at risk of being infected, alert them and impose quarantine, a measure of social isolation that prevents the potential spread. So far, much has been said about which professionals should perform this screening but Little about how it should be done. In this article, in the first place, it is defined what tracking is, which professionals are best prepared for the use of scientific methodologies that support tracking word. From the scientific literature that analyzes how socialization affects the spread, a simulation is developed on how COVID 19 can spread during the social interactions of people in their different areas of socialization. On this simulation, social network analysis and certain algorithms for community detection and cohesion analysis are used to show the suitability of these methodologies for tracking. The results show that with the support of social network analysis and certain algorithms, key information about communities formed in the network structure and who are the super-propagators and intermediaries between the detected communities is accessed early. This can help prioritize contacting these people to cut the chains of community transmission. Finally, we discuss the suitability for Social Work professionals to be trained in these methodologies in order to develop this tracking work.

Social Network Models for Enhancing Reference-Based Search Engine Rankings

2011 ◽  
pp. 109-133 ◽  
Author(s):  
Nikolaos Korfiatis ◽  
Miguel-Ángel Sicilia ◽  
Claudia Hess ◽  
Klaus Stein ◽  
Christoph Schlieder
Keyword(s):  
Information Retrieval ◽  
Social Network ◽  
Social Context ◽  
Search Engine ◽  
Web Search ◽  
Network Models ◽  
Reference Network ◽  
Ranking Models ◽  
The Social ◽  
Network Metrics

This chapter discusses the integration of information retrieval information from two sources: a social network and a document reference network, for enhancing reference based search engine rankings. In particular, current models of information retrieval are blind to the social context that surrounds information resources thus do not consider the trustworthiness of their authors when they present the query results to the users. Following this point we elaborate on the basic intuitions that highlight the contribution of the social context – as can be mined from social network positions for instance – into the improvement of the rankings provided in reference based search engines. A review on ranking models in web search engine retrieval along with social network metrics of importance such as prestige and centrality is provided as a background. Then a presentation of recent research models that utilize both contexts is provided along with a case study in the internet based encyclopedia Wikipedia based on the social network metrics.

The use of social networks in marketing: the Italian co-operative experience

2015 ◽  
Vol 7 (1) ◽  
pp. 31-57 ◽  
Author(s):  
Patrizia Battilani ◽  
Giuliana Bertagnoni
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Marketing Strategy ◽  
Local Community ◽  
National Level ◽  
Viral Marketing ◽  
Original Research ◽  
Content Type ◽  
The Social

Purpose – The main aim of our study is to demonstrate that the Italian way to marketing included not only the “advertising artists” but also what can be labelled as the social network approach, which was mainly used by cooperative enterprises. Focussing on the case study of the Granarolo co-operative, the paper discusses the social network method of marketing as it emerged during the 1950s and 1960s in Italy. Design/methodology/approach – The research draws on different types of primary sources, including co-operative business records, interviews, publications, newspaper articles and advertisements. Findings – In the age of mass consumption, the Granarolo co-operative developed an original marketing strategy based on social networks. This strategy can be considered a kind of community brand based on shared values pre-existing to the brand itself and a kind of viral marketing put in place before the electronic revolution. Research limitations/implications – The research focusses on the Granarolo case study. It can be extended to other co-operative enterprises. However, it is unknown whether the anticipation of viral marketing has also been used by private enterprises. Practical implications – The marketing strategies analyzed in the paper could be a interesting solution for undertakings strictly connected and rooted in their local community or in their Web community. Social implications – In today’s world of the Web, this physical constraint no longer exists, and the social method of marketing exceeds the regional and even the national level. In conclusion, this was an innovative method of marketing and advertising that came into being, ahead of its time, about a half a century before modern Web-based social networks were conceived, yet uses the same concepts, hence its extraordinary originality. Originality/value – This study is the result of an original research which tries to highlight what we could label the Italian way to marketing. Taking into consideration the first two decades of the Granarolo history and focussing on the marketing strategy, our contribution seeks to examine how the social networks approach worked and in what it differs from today brand community and viral marketing.

The social network

2013 ◽  
Vol 44 (2) ◽  
pp. 22
Author(s):  
ALAN ROCKOFF
Keyword(s):  
Social Network ◽  
The Social
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