Measuring ego-centered social networks

In measuring ego-centered social networks, two general approaches can be distinguished. A very simple way to evaluate membership in a social network is to ask an ordinary survey question where response categories are types of relationships (e.g., partner, parents, children, friends, etc.). This approach (usually called the role relation(ship) approach) is very appealing as it saves time and money. However, information obtained by this approach is very limited. Most often, when evaluating ego-centered networks, the name generator approach is used. The list of egos (respondents) is obtained in the first step. In the second step, existing ties are identified - all alters with whom the focal ego has some sort of relationship. When all ties have been identified, the contents and the characteristics of ties are assessed. In most cases the characteristics of the alters are also measured. The name generator approach yields more data and is also of higher quality. However, it is time and money consuming, and it requires either considerable effort from respondents, when it is applied in self-administered mode, or complex coordination between interviewer and respondent, when it is applied in personal interviews (e.g., Kogovšek et al., 2002). In a series of studies (e.g., Hlebec and Kogovšek, 2005; Kogovšek and Hlebec, 2005; Kogovšek and Hlebec, 2008), network composition was estimated using both approaches. Test-retest and split-ballot experiments on convenience samples of respondents were used to assess the stability of network composition. Findings show that, with some caution, the two approaches are comparable. In the present paper this line of research is taken a step further. Typologies of social support networks are produced by hierarchical clustering on the basis of network composition, estimated by both approaches. Overall stability of typologies as well as stability of clustering of individual respondents is studied by means of simple descriptive analyses and by discriminant analysis. The results show that the overall stability of typologies is relatively high – two to three cluster groups are obtained in each analysis. However, the typologies seem to be more stable in one experimental group. Also the stability of clustering for individual respondents seems quite high as 73% to 85% of respondents were correctly classified. Incorrectly classified respondents were also studied, but their characteristics may well reflect the specific characteristics of the sampling procedure rather than some other systematic factor.

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The Usage of Social Network to Students: Does It Improve Student’s Education Quality During COVID-19 Outbreak

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2020.9412 ◽

2020 ◽

Vol 17 (12) ◽

pp. 5224-5228

Author(s):

Indraah Kolandaisamy ◽

Raenu Kolandaisamy

Keyword(s):

Social Networks ◽

Social Network ◽

Education Quality ◽

Quality Of Education ◽

Online Classes ◽

Outbreak Period ◽

Technology Advancement ◽

The Relationship

In the era of technology advancement and COVID-19 outbreak period, all physical classes have been converted to online classes through social network platforms. Having online classes through social networks are actually very comfortable and flexible for students as they can have their classes at various places. This paper is focuses on the relationship between usages of social network and the quality of education during COVID-19 outbreak.

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A Usability Evaluation of Facebook's Privacy Features Based on the Perspectives of Experts and Users

Censorship, Surveillance, and Privacy ◽

10.4018/978-1-5225-7113-1.ch076 ◽

2019 ◽

pp. 1544-1568

Author(s):

Márcio J. Mantau ◽

Marcos H. Kimura ◽

Isabela Gasparini ◽

Carla D. M. Berkenbrock ◽

Avanilde Kemczinski

Keyword(s):

Social Networks ◽

Social Media ◽

Social Network ◽

User Interaction ◽

Usability Evaluation ◽

Second Step ◽

Web Based ◽

The Third ◽

Privacy Settings ◽

Three Stages

The issue of privacy in social networks is a hot topic today, because of the growing amount of information shared among users, who are connected to social media every moment and by different devices and displays. This chapter presents a usability evaluation of the privacy features of Facebook's social network. The authors carry out an evaluation composed by three approaches, executed in three stages: first by the analysis and inspection of system's features related to privacy, available for both systems (Web-based systems and mobile-based systems, e.g. app). The second step is a heuristic evaluation led by three experts, and finally, the third step is a questionnaire with 605 users to compare the results between specialists and real users. This chapter aims to present the problems associated with these privacy settings, and it also wants to contribute for improving the user interaction with this social network.

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Unraveling the Taste Fabric of Social Networks

Human Computer Interaction ◽

10.4018/978-1-87828-991-9.ch096 ◽

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.

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EXPANDING SOCIAL TIES AS A GOAL IN LATER LIFE: THE ROLE OF SOCIAL NETWORK CHARACTERISTICS

Innovation in Aging ◽

10.1093/geroni/igz038.623 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

pp. S175-S175

Author(s):

Danielle Oleskiewicz ◽

Karen Rook

Keyword(s):

Older Adults ◽

Social Networks ◽

Social Network ◽

Social Ties ◽

Later Life ◽

Well Being ◽

Support Provision ◽

Network Characteristics ◽

Network Composition

Abstract Older adults often winnow their social ties to focus on emotionally rewarding ties (Charles & Carstensen, 2010). Some older adults, however, have small social networks that preclude much winnowing or aversive social ties from which disengagement is difficult. These individuals might be motivated to expand, rather than contract, their social ties. The current study sought to extend knowledge regarding potential links between social network characteristics and older adults’ interest, effort, and success in creating new social ties. We expected that small social networks and negative social ties might motivate interest and effort directed toward forming new social ties but that positive social ties might foster success in efforts to form new ties. In-person interviews were conducted with participants (N = 351, Mean age = 74.16) in a larger study of older adults’ social networks and well-being. The interviews assessed participants’ social networks, as well as their interest, effort, and success in making new social ties. Participants’ social network composition, rather than size, was associated with greater motivation to establish new social ties. Negative social ties were associated with greater interest and effort directed toward forming new social ties. Positive social ties were related to greater success (due, in part, to their support provision) and, unexpectedly, were also related to greater interest and effort directed toward forming new ties. Older adults sometimes seek to expand, rather than contract, their social ties, and characteristics of their social networks appear to play a role in fueling and influencing the success of such efforts.

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Visual Dynamic Simulation Model of Unstructured Data in Social Networks

Security and Communication Networks ◽

10.1155/2022/9095330 ◽

2022 ◽

Vol 2022 ◽

pp. 1-10

Author(s):

Zhang Xiang

Keyword(s):

Social Networks ◽

Social Network ◽

Simulation Model ◽

Dynamic Simulation ◽

Data Visualization ◽

Time Correlation ◽

Unstructured Data ◽

Dynamic Simulation Model ◽

Visualization Technology ◽

The Stability

Social networks contain a large amount of unstructured data. To ensure the stability of unstructured big data, this study proposes a method for visual dynamic simulation model of unstructured data in social networks. This study uses the Hadoop platform and data visualization technology to establish a univariate linear regression model according to the time correlation between data, estimates and approximates perceptual data, and collects unstructured data of social networks. Then, the unstructured data collected from the original social network are processed, and an adaptive threshold is designed to filter out the influence of noise. The unstructured data of social network after feature analysis are processed to extract its visual features. Finally, this study carries out the Hadoop cluster design, implements data persistence by HDFS, uses MapReduce to extract data clusters for distributed computing, builds a visual dynamic simulation model of unstructured data in social network, and realizes the display of unstructured data in social network. The experimental results show that this method has a good visualization effect on unstructured data in social networks and can effectively improve the stability and efficiency of unstructured data visualization in social networks.

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How to make methodological decisions when inferring social networks

10.1101/739789 ◽

2019 ◽

Author(s):

André C. Ferreira ◽

Rita Covas ◽

Liliana R. Silva ◽

Sandra C. Esteves ◽

Inês F. Duarte ◽

...

Keyword(s):

Social Networks ◽

Social Network ◽

Data Collection ◽

Network Inference ◽

A Priori ◽

Pilot Studies ◽

Multiple Hypotheses Testing ◽

Sociable Weavers ◽

Breeding Groups

ABSTRACTConstructing and analysing social networks data can be challenging. When designing new studies, researchers are confronted with having to make decisions about how data are collected and networks are constructed, and the answers are not always straightforward. The current lack of guidance on building a social network for a new study system might lead researchers to try several different methods, and risk generating false results arising from multiple hypotheses testing. We suggest an approach for making decisions when developing a network without jeopardising the validity of future hypothesis tests. We argue that choosing the best edge definition for a network can be made using a priori knowledge of the species, and testing hypotheses that are known and independent from those that the network will ultimately be used to evaluate. We illustrate this approach by conducting a pilot study with the aim of identifying how to construct a social network for colonies of cooperatively breeding sociable weavers. We first identified two ways of collecting data using different numbers of feeders and three ways to define associations among birds. We then identified which combination of data collection and association definition maximised (i) the assortment of individuals into ‘breeding groups’ (birds that contribute towards the same nest and maintain cohesion when foraging), and (ii) socially differentiated relationships (more strong and weak relationships than expected by chance). Our approach highlights how existing knowledge about a system can be used to help navigate the myriad of methodological decisions about data collection and network inference.SIGNIFICANCE STATEMENTGeneral guidance on how to analyse social networks has been provided in recent papers. However less attention has been given to system-specific methodological decisions when designing new studies, specifically on how data are collected, and how edge weights are defined from the collected data. This lack of guidance can lead researchers into being less critical about their study design and making arbitrary decisions or trying several different methods driven by a given preferred hypothesis of interest without realising the consequences of such approaches. Here we show that pilot studies combined with a priori knowledge of the study species’ social behaviour can greatly facilitate making methodological decisions. Furthermore, we empirically show that different decisions, even if data are collected under the same context (e.g. foraging), can affect the quality of a network.

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Social Network and Healthy Ageing among Elderly in Helping Hearts Old Age Home, Coimbatore

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.l1141.10812s19 ◽

2019 ◽

Vol 8 (12S) ◽

pp. 571-576

Keyword(s):

Social Networks ◽

Social Network ◽

Social Participation ◽

Meaning In Life ◽

Well Being ◽

The Elderly ◽

Healthy Ageing ◽

The Social ◽

The Relationship

In the current times, the research cites that elderly definitely need social networks to aid in their mental and physical well being. The previous researches have indicated familyfocused, friend-focused, and restricted types as the types of social networks available. Social network include social interaction and social communication. It is the need of the hour to study about the social network of the elderly population because many of them are left with nobody and loneliness is one of the important factor not to mention about desertion by their loved ones since they are no longer productive individuals. The heterogeneity of social networks is pathway to successful and healthy ageing. Healthy ageing is about using opportunities so that they can have social participation and lead a good quality of life. Elderly need not be burdensome individuals in the society instead they can be involved in lot of activities which contribute to them ageing gracefully. The research studies state that rural elderly have more chances of social participation that they find more meaning in life which is a contributing factor for healthy ageing. The present study aims to find out the relationship between social network and healthy ageing.

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Extracting Influential Nodes in Social Networks on Local Weight Aspect

International Journal of Interdisciplinary Telecommunications and Networking ◽

10.4018/ijitn.2016040103 ◽

2016 ◽

Vol 8 (2) ◽

pp. 21-35

Author(s):

Jun Jun Cheng ◽

Yan Chao Zhang ◽

Xin Zhou ◽

Hui Cheng

Keyword(s):

Social Networks ◽

Social Network ◽

Time Complexity ◽

Heuristic Algorithms ◽

Transmission Model ◽

User Interest ◽

Local Weight ◽

Weight Index ◽

Influential Nodes

Studies have shown that influential nodes play an important role in all kinds of dynamic behavior in the complex network. Excavation or recognition of such nodes contributes to the development of application areas such as social network advertising and user interest recommendation. Although some heuristic algorithms such as degree, betweenness, closeness and k-shell (or k-core) can identify influential nodes at the same time, they are disadvantaged in terms of accuracy and time complexity. Based on this, the authors propose a novel local weight index to distinguish the node influence based on the theory of ties strength. This index emphasizes that the node influence is jointly decided by the quantity and quality of the neighbors, and its time complexity is much lower than closeness and betweenness. With the aid of SIR information transmission model, this paper verifies the validity of local weight index.

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Unraveling the Taste Fabric of Social Networks

Social Networking Communities and E-Dating Services ◽

10.4018/978-1-60566-104-9.ch002 ◽

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.

Download Full-text