scholarly journals Cues to gender and racial identity reduce creativity in diverse social networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Raiyan Abdul Baten ◽  
Richard N. Aslin ◽  
Gourab Ghoshal ◽  
Ehsan Hoque
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Racial Identity ◽  
Randomized Experiment ◽  
Prior Work ◽  
Group Interactions ◽  
Demographic Groups ◽  
Racial Identities ◽  
Dynamic Social Network ◽  
Social Partners

AbstractThe characteristics of social partners have long been hypothesized as influential in guiding group interactions. Understanding how demographic cues impact networks of creative collaborators is critical for elevating creative performances therein. We conducted a randomized experiment to investigate how the knowledge of peers’ gender and racial identities distorts people’s connection patterns and the resulting creative outcomes in a dynamic social network. Consistent with prior work, we found that creative inspiration links are primarily formed with top idea-generators. However, when gender and racial identities are known, not only is there (1) an increase of $$82.03\%$$ 82.03 % in the odds of same-gender connections to persist (but not for same-race connections), but (2) the semantic similarity of idea-sets stimulated by these connections also increase significantly compared to demography-agnostic networks, negatively impacting the outcomes of divergent creativity. We found that ideas tend to be significantly more homogeneous within demographic groups than between, taking away diversity-bonuses from similarity-based links and partly explaining the results. These insights can inform intelligent interventions to enhance network-wide creative performances.

Limitation of degree information for analyzing the interaction evolution in online social networks

2014 ◽  
Vol 25 (10) ◽  
pp. 1450056 ◽  
Author(s):  
Ke-Ke Shang ◽  
Wei-Sheng Yan ◽  
Xiao-Ke Xu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Services ◽  
Online Social Networks ◽  
Dynamic Network ◽  
Interaction Network ◽  
Strength Distribution ◽  
Customer Churn ◽  
Dynamic Social Network ◽  
Temporal Interactions

Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.

Social Networks and Crime: Pitfalls and Promises for Advancing the Field

2019 ◽  
Vol 2 (1) ◽  
pp. 99-122 ◽  
Author(s):  
Katherine Faust ◽  
George E. Tita
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Potential Measurement ◽  
Fully Integrated ◽  
Social Network Data ◽  
The Past ◽  
Dynamic Social Network ◽  
Criminological Research ◽  
The Social ◽  
Criminological Theories

Over the past decade, a considerable literature has emerged within criminology stemming from the collection of social network data and the adoption of social network analysis by a cadre of scholars. We review recent contributions to four areas of crime research: co-offending networks, illicit networks, gang-rivalry networks, and neighborhoods and crime. Our review highlights potential pitfalls that one might encounter when using social networks in criminological research and points to fruitful directions for further research. In particular, we recommend paying special attention to the clear specifications of what ties in the network are assumed to be doing, potential measurement weaknesses that can arise when using police or investigative data to construct a network, and understanding dynamic social network processes related to criminological outcomes. We envision a bright future in which the social network perspective will be more fully integrated into criminological theories, analyses, and applications.

scholarly journals The Measurement of Demographic Temperature Using the Sentiment Analysis of Data from the Social Network VKontakte

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 987
Author(s):  
Irina Evgenievna Kalabikhina ◽  
Evgeniy Petrovich Banin ◽  
Imiliya Abduselimovna Abduselimova ◽  
German Andreevich Klimenko ◽  
Anton Vasilyevich Kolotusha
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Social Network ◽  
Sentiment Analysis ◽  
Russian Language ◽  
Temperature Ratio ◽  
Additional Result ◽  
Demographic Groups ◽  
The Social ◽  
Negative Comments

Social networks have a huge potential for the reflection of public opinion, values, and attitudes. In this study, the presented approach can allow to continuously measure how cold “the demographic temperature” is based on data taken from the Russian social network VKontakte. This is the first attempt to analyze the sentiment of Russian-language comments on social networks to determine the demographic temperature (ratio of positive and negative comments) in certain socio-demographic groups of social network users. The authors use generated data from the comments to posts from 314 pro-natalist groups (with child-born reproductive attitudes) and eight anti-natalist groups (with child-free reproductive attitudes) on the demographic topic, which have 9 million of users from all over Russia. The algorithm of the sentiment analysis for demographic tasks is presented in the article. In particularly, it was found that comments under posts are more suitable for analyzing the sentiment of statements than the texts of posts. Using the available data in two types of groups since 2014, we find an asynchronous structural shift in comments of the corpuses of pro-natalist and anti-natalist thematic groups. Interpretations of the evidences are offered in the discussion part of the article. An additional result of our work is two open Russian-language datasets of comments on social networks.

Applications of Data Mining in Dynamic Social Network Analysis

2013 ◽  
pp. 110-121
Author(s):  
Manish Kumar
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Networking ◽  
Knowledge Discovery ◽  
Online Social Networking ◽  
Dynamic Social Network ◽  
Business Goals

Social Networks are nodes consisting of people, groups and organizations growing dynamically. The growth is horizontal as well as vertical in terms of size and number. Social network analysis has gained success due to online social networking and sharing sites. The accessibility of online social sites such as MySpace, Facebook, Twitter, Hi5, Friendster, SkyRock and Beb offer sharing and maintaining large amount of different data. Social network analysis is focused on mining such data i.e. generating pattern of people’s interaction. The analysis involves the knowledge discovery that helps the sites as well as users in terms of usage and business goals respectively. Further it is desired that the process must be privacy preserving. This chapter describes the various mining techniques applicable on social networks data.

A NOVEL FRAMEWORK FOR TRACKING ONLINE COMMUNITY INTERACTION IN SOCIAL NETWORK

2013 ◽  
Vol 09 (02) ◽  
pp. 1350011
Author(s):  
SANJIV SHARMA ◽  
G. N. PUROHIT
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Community ◽  
Community Interaction ◽  
Dynamic Social Network ◽  
Meaningful Group ◽  
Group Structures

This paper focuses on a design of improved framework and analysis of existing framework which exploits certain algorithms for tracking online community in social network. Tracking of online community is an imperative task where the goal is to identify meaningful group structures in the dynamic social network and consider the problem of the evolution of groups of users in dynamic scenarios. Existing frameworks for tracking community in social network have some limitation which makes it less scalable and computationally inefficient. This novel framework facilitates scalable tracking communities over the time in social networks and offers efficient methods to deal with the problems which are offered in most of the existing frameworks.

Finding Communities and Their Evolutions in Dynamic Social Network

2012 ◽  
Author(s):  
Tianbao Yang ◽  
Shenghuo Zhu ◽  
Yun Chi ◽  
Yihong Gong
Keyword(s):  
Social Network ◽  
Dynamic Social Network

Emotive Trending And Tracking of Tweets

2017 ◽  
Vol 7 (11) ◽  
pp. 25
Author(s):  
Sanjay Chhataru Gupta
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
The Social ◽  
The World ◽  
Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

Social Networks and Business Performance of Igbo Migrant Traders in Ibadan, South-West Nigeria

2014 ◽  
Vol 12 (2) ◽  
Author(s):  
Deborah O. Obor ◽  
Emeka E. Okafor
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Social Network ◽  
Social Exchange ◽  
Business Performance ◽  
Exploratory Research ◽  
Business Growth ◽  
South West ◽  
Key Informant ◽  
Depth Interviews

This study focused on social networks and business performance among Igbo businessmen in Ibadan, South-west Nigeria through the exploratory research design. Social exchange, social network and social capital theories were employed as theoretical framework. Twenty-six in-depth interviews, key informant interviews and case studies were conducted with purposively selected respondents in four business locations in Ibadan. The results showed that among the factors that facilitated migration of the Igbo to Ibadan were their interest to learn a trade, their inability to attain higher education, and having a relative in Ibadan. The types of social networks available showed that social network was not location bound, as all the respondents belonged to town progressive unions and mutual benefits/cooperative associations. Social networks played vital roles in business performance, including social support, access to loan, business growth and expansion. The main challenges to maintaining adequate social network in business were distrust, envy, unbridled competition, dishonesty and inability to keep terms of agreement. The study concludes that social networks have positively influenced the business performance of migrant Igbo in Ibadan. There is need for the Igbo to strengthen their social networks through honesty, forthrightness, and transparency in all their dealings.

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