Unraveling the Taste Fabric of Social Networks

2009 ◽  
pp. 18-43
Author(s):  
Hugo Liu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Social Connectedness ◽  
Natural Language Text ◽  
Cross Domain ◽  
Semantic Mining ◽  
The Rich ◽  
Language Text

Popular online social networks such as Friendster and MySpace do more than simply reveal the superficial structure of social connectedness — the rich meanings bottled within social network profiles themselves imply deeper patterns of culture and taste. If these latent semantic fabrics of taste could be harvested formally, the resultant resource would afford completely novel ways for representing and reasoning about web users and people in general. This paper narrates the theory and technique of such a feat — the natural language text of 100,000 social network profiles were captured, mapped into a diverse ontology of music, books, films, foods, etc., and machine learning was applied to infer a semantic fabric of taste. Taste fabrics bring us closer to improvisational manipulations of meaning, and afford us at least three semantic functions — the creation of semantically flexible user representations, cross-domain taste-based recommendation, and the computation of taste-similarity between people — whose use cases are demonstrated within the context of three applications — the InterestMap, Ambient Semantics, and IdentityMirror. Finally, we evaluate the quality of the taste fabrics, and distill from this research reusable methodologies and techniques of consequence to the semantic mining and Semantic Web communities.

Unraveling the Taste Fabric of Social Networks

2009 ◽  
pp. 1521-1546
Author(s):  
Hugo Liu ◽  
Pattie Maes ◽  
Glorianna Davenport
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Social Connectedness ◽  
Natural Language Text ◽  
Cross Domain ◽  
Semantic Mining ◽  
The Rich ◽  
Language Text

Popular online social networks such as Friendster and MySpace do more than simply reveal the superficial structure of social connectedness—the rich meanings bottled within social network profiles themselves imply deeper patterns of culture and taste. If these latent semantic fabrics of taste could be harvested formally, the resultant resource would afford completely novel ways for representing and reasoning about web users and people in general. This paper narrates the theory and technique of such a feat—the natural language text of 100,000 social network profiles were captured, mapped into a diverse ontology of music, books, films, foods, etc., and machine learning was applied to infer a semantic fabric of taste. Taste fabrics bring us closer to improvisational manipulations of meaning, and afford us at least three semantic functions—the creation of semantically flexible user representations, cross-domain taste-based recommendation, and the computation of taste-similarity between people— whose use cases are demonstrated within the context of three applications—the InterestMap, Ambient Semantics, and IdentityMirror. Finally, we evaluate the quality of the taste fabrics, and distill from this research reusable methodologies and techniques of consequence to the semantic mining and Semantic Web communities.

Unraveling the Taste Fabric of Social Networks

2009 ◽  
pp. 256-282 ◽  
Author(s):  
Hugo Liu ◽  
Pattie Maes ◽  
Glorianna Davenport
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Social Connectedness ◽  
Natural Language Text ◽  
Semantic Mining ◽  
The Rich ◽  
Language Text

Popular online social networks such as Friendster and MySpace do more than simply reveal the superficial structure of social connectedness — the rich meanings bottled within social network profiles themselves imply deeper patterns of culture and taste. If these latent semantic fabrics of taste could be harvested formally, the resultant resource would afford completely novel ways for representing and reasoning about web users and people in general. This paper narrates the theory and technique of such a feat — the natural language text of 100,000 social network profiles were captured, mapped into a diverse ontology of music, books, films, foods, etc., and machine learning was applied to infer a semantic fabric of taste. Taste fabrics bring us closer to improvisational manipulations of meaning, and afford us at least three semantic functions — the creation of semantically flexible user representations, crossdomain taste-based recommendation, and the computation of taste-similarity between people — whose use cases are demonstrated within the context of three applications — the InterestMap, Ambient Semantics, and IdentityMirror. Finally, we evaluate the quality of the taste fabrics, and distill from this research reusable methodologies and techniques of consequence to the semantic mining and Semantic Web communities.

Preventing Identity Disclosure in Social Networks Using Intersected Node

2016 ◽  
Vol 10 (3) ◽  
pp. 25-41 ◽  
Author(s):  
Amardeep Singh ◽  
Divya Bansal ◽  
Sanjeev Sofat
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Privacy And Security ◽  
Identity Disclosure ◽  
The Social ◽  
Confidential Data ◽  
Noise Nodes ◽  
Graphical Structure

Social networks like Facebook, Twitter, Pinterest etc. provide data of its users to the demanding organizations to better comprehend the quality of their potential clients. Publishing confidential data of social network users in its raw form raises several privacy and security concerns. Recently, some anonymization techniques have been developed to address these issues. In this paper, a technique to prevent identity disclosure through structure attacks has been proposed which not only prevents identity disclosure but also preserves utility of data published by online social networks. Algorithms have been developed by using noise nodes/edges with the consideration of introducing minimum change in the original graphical structure of social networks. The authors' work is unique in the sense that previous works are based on edge editing only but their proposed work protects against structure attacks using mutual nodes in the social network and the effectiveness of the proposed technique has been proved using APL (Average Path Length) and information loss as parameters.

Accessibility and communicability on Facebook: A case study with Brazilian elderly

First Monday ◽  
2019 ◽  
Author(s):  
Carolina Sacramento ◽  
Simone Bacellar Leal Ferreira ◽  
Eliane Pinheiro Capra ◽  
Ana Cristina Bicharra Garcia
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Interaction ◽  
Online Social Networks ◽  
Elderly Population ◽  
The Elderly ◽  
Virtual Spaces ◽  
Older Users

Given the growth of the elderly population, it is essential that online social networks consider aspects of quality of use to address the unique needs of this audience. Unfortunately, networks, such as Facebook, have been designed largely for younger users, leading to challenges for the elderly in the use of their interfaces.Some human–computer interaction (HCI) research has explored the usability and accessibility of Facebook and its functionalities, including for the elderly. However, there has not been a great deal of research exploring communicability of this social network Facebook for older users. This paper presents the results of a 2015 case study completed in Brazil, in which Facebook’s accessibility and communicability for the elderly were analyzed. As a result of this research, checkpoints are presented to support designers in the construction of virtual spaces for social interaction.

The Oxford Handbook of Social Networks

2020 ◽  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Life ◽  
Information Science ◽  
Computational Social Science ◽  
The Social ◽  
Diverse Field ◽  
The Rich

Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.

scholarly journals How migrants manifest their transnational identity through online social networks: comparative findings from a case of Koreans in Germany

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Sunyoung Park ◽  
Lasse Gerrits
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Online Social Network ◽  
Point Of View ◽  
Comparative Case Study ◽  
Transnational Identity ◽  
Transnational Identities ◽  
Web 3.0 ◽  
Situational Contexts

AbstractAlthough migration has long been an imperative topic in social sciences, there are still needs of study on migrants’ unique and dynamic transnational identity, which heavily influences the social integration in the host society. In Online Social Network (OSN), where the contemporary migrants actively communicate and share their stories the most, different challenges against migrants’ belonging and identity and how they cope or reconcile may evidently exist. This paper aims to scrutinise how migrants are manifesting their belonging and identity via different technological types of online social networks, to understand the relations between online social networks and migrants’ multi-faceted transnational identity. The research introduces a comparative case study on an online social movement led by Koreans in Germany via their online communities, triggered by a German TV advertisement considered as stereotyping East Asians given by white supremacy’s point of view. Starting with virtual ethnography on three OSNs representing each of internet generations (Web 1.0 ~ Web 3.0), two-step Qualitative Data Analysis is carried out to examine how Korean migrants manifest their belonging and identity via their views on “who we are” and “who are others”. The analysis reveals how Korean migrants’ transnational identities differ by their expectation on the audience and the members in each online social network, which indicates that the distinctive features of the online platform may encourage or discourage them in shaping transnational identity as a group identity. The paper concludes with the two main emphases: first, current OSNs comprising different generational technologies play a significant role in understanding the migrants’ dynamic social values, and particularly, transnational identities. Second, the dynamics of migrants’ transnational identity engages diverse social and situational contexts. (keywords: transnational identity, migrants’ online social networks, stereotyping migrants, technological evolution of online social network).

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.

Personality, risk tolerance and social network use: an exploratory study

2016 ◽  
Vol 42 (6) ◽  
pp. 536-552 ◽  
Author(s):  
Shaista Wasiuzzaman ◽  
Siavash Edalat
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Financial Risk ◽  
Ordinary Least Squares ◽  
Risk Tolerance ◽  
Network Activity ◽  
Least Squares Regression ◽  
Content Type ◽  
Financial Risk Tolerance

Purpose – The vast amount of information available via online social networks (OSN) makes it a very good avenue for understanding human behavior. One of the human characteristics of interest to financial practitioners is an individual’s financial risk tolerance. The purpose of this paper is to look at the relationship between an individual’s OSN behavior and his/her financial risk tolerance. Design/methodology/approach – The study uses data collected from a sample of 220 university students and the backward variables selection ordinary least squares regression analysis technique to achieve its objective. Findings – The results of the study find that the frequency of logging on to social network sites indicates an individual who has higher financial risk tolerance. Additionally, the increasing use of social networks for social connection is found to be associated with lower financial risk tolerance. The results are mostly consistent when the sample is split based on prior financial knowledge. Originality/value – To the authors’ knowledge this is the first study which documents the possibility of understanding an individual’s financial risk tolerance via his/her social network activity. This provides investment/financial consultants with more avenues for gathering information in order to understand their current or potential clients hence providing better services.

scholarly journals IMPACT OF OFFLINE AND ONLINE SOCIAL NETWORKS ON LONELINESS AND MENTAL HEALTH AMONG ITALIAN OLDER PEOPLE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S529-S529
Author(s):  
Daniele Zaccaria ◽  
Georgia Casanova ◽  
Antonio Guaita
Keyword(s):  
Mental Health ◽  
Social Networks ◽  
Social Network ◽  
Older People ◽  
Online Social Networks ◽  
Social Network Sites ◽  
Well Being ◽  
Controlled Study ◽  
Face To Face ◽  
Causal Impact

Abstract In the last decades the study of older people and social networks has been at the core of gerontology research. The literature underlines the positive health effects of traditional and online social connections and also the social networks’s positive impact on cognitive performance, mental health and quality of life. Aging in a Networked Society is a randomized controlled study aimed at investigating causal impact of traditional face-to-face social networks and online social networks (e.g. Social Network Sites) on older people’ health, cognitive functions and well-being. A social experiment, based on a pre-existing longitudinal study (InveCe - Brain Aging in Abbiategrasso) has involved 180 older people born from 1935 to 1939 living in Abbiategrasso, a municipality near Milan. We analyse effects on health and well-being of smartphones and Facebook use (compared to engagement in a more traditional face-to-face activity), exploiting the research potential of past waves of InveCe study, which collected information concerning physical, cognitive and mental health using international validate scale, blood samples, genetic markers and information on social networks and socio-demographic characteristics of all participants. Results of statistical analysis show that poor social relations and high level of perceived loneliness (measured by Lubben Scale and UCLA Loneliness scale) affect negatively physical and mental outcomes. We also found that gender and marital status mediate the relationship between loneliness and mental wellbeing, while education has not significant effect. Moreover, trial results underline the causal impact of ICT use (smartphones, internet, social network sites) on self-perceived loneliness and cognitive and physical health.

Quantifying Virality of Information in Online Social Networks

2012 ◽  
Vol 4 (1) ◽  
pp. 32-45 ◽  
Author(s):  
Abhishek Vaish ◽  
Rajiv Krishna G. ◽  
Akshay Saxena ◽  
Dharmaprakash M. ◽  
Utkarsh Goel
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Online Social Network ◽  
Critical Factors ◽  
Asset Valuation ◽  
Valuation Technique ◽  
Information Item ◽  
Viral Nature ◽  
Over Time

The aim of this research is to propose a model through which the viral nature of an information item in an online social network can be quantified. Further, the authors propose an alternate technique for information asset valuation by accommodating virality in it which not only complements the existing valuation system, but also improves the accuracy of the results. They use a popularly available YouTube dataset to collect attributes and measure critical factors such as share-count, appreciation, user rating, controversiality, and comment rate. These variables are used with a proposed formula to obtain viral index of each video on a given date. The authors then identify a conventional and a hybrid asset valuation technique to demonstrate how virality can fit in to provide accurate results.The research demonstrates the dependency of virality on critical social network factors. With the help of a second dataset acquired, the authors determine the pattern virality of an information item takes over time.

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