A Field Study on Matching with Network Externalities

Does civic participation lead to a large social network? This study claims that high levels of civic participation may obstruct individual social embeddedness. Using survey data from the German Survey on Volunteering (Deutscher Freiwilligensurvey; 1999–2009), this study conducts macro- as well as multi-level regressions to examine the link between civic participation and social embeddedness. Findings reveal that civic participation on the sub-national regional level is not generally associated with social embeddedness, but it affects the participants’ and non-participants’ possibilities for friendships differently. This holds especially true in urban areas, but the effect cannot be found in rural areas. The analysis has implications for further research to enhance the social embeddedness of the excluded.

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The Value of Price Discrimination in Large Social Networks

Management Science ◽

10.1287/mnsc.2021.4108 ◽

2021 ◽

Author(s):

Jiali Huang ◽

Ankur Mani ◽

Zizhuo Wang

Keyword(s):

Social Networks ◽

Social Network ◽

Price Discrimination ◽

Consumer Satisfaction ◽

Numerical Experiments ◽

Network Externalities ◽

Random Networks ◽

Positive Externalities ◽

The Social ◽

Recent Trends

We study the value of price discrimination in large social networks. Recent trends in industry suggest that, increasingly, firms are using information about social network to offer personalized prices to individuals based upon their positions in the social network. In the presence of positive network externalities, firms aim to increase their profits by offering discounts to influential individuals that can stimulate consumption by other individuals at a higher price. However, the lack of transparency in discriminative pricing may reduce consumer satisfaction and create mistrust. Recent research focuses on the computation of optimal prices in deterministic networks under positive externalities. We want to answer the question of how valuable such discriminative pricing is. We find, surprisingly, that the value of such pricing policies (increase in profits resulting from price discrimination) in very large random networks are often not significant. Particularly, for Erdös–Renyi random networks, we provide the exact rates at which this value decays in the size of the networks for different ranges of network densities. Our results show that there is a nonnegligible value of price discrimination for a small class of moderate-sized Erdös–Renyi random networks. We also present a framework to obtain bounds on the value of price discrimination for random networks with general degree distributions and apply the framework to obtain bounds on the value of price discrimination in power-law networks. Our numerical experiments demonstrate our results and suggest that our results are robust to changes in the model of network externalities. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.

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Is Bigger Always Better? Potential Biases of Big Data Derived from Social Network Sites

The Annals of the American Academy of Political and Social Science ◽

10.1177/0002716215570866 ◽

2015 ◽

Vol 659 (1) ◽

pp. 63-76 ◽

Cited By ~ 88

Author(s):

Eszter Hargittai

Keyword(s):

Socioeconomic Status ◽

Big Data ◽

Social Network ◽

Survey Data ◽

Social Network Sites ◽

Biased Sampling ◽

Methodological Challenges ◽

Internet Skills ◽

The Social ◽

Race Ethnicity

This article discusses methodological challenges of using big data that rely on specific sites and services as their sampling frames, focusing on social network sites in particular. It draws on survey data to show that people do not select into the use of such sites randomly. Instead, use is biased in certain ways yielding samples that limit the generalizability of findings. Results show that age, gender, race/ethnicity, socioeconomic status, online experiences, and Internet skills all influence the social network sites people use and thus where traces of their behavior show up. This has implications for the types of conclusions one can draw from data derived from users of specific sites. The article ends by noting how big data studies can address the shortcomings that result from biased sampling frames.

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A Pilot Study of Comparing Social Network Behaviors between Onlies and Others

International Journal of Cyber Behavior Psychology and Learning ◽

10.4018/ijcbpl.2015070105 ◽

2015 ◽

Vol 5 (3) ◽

pp. 56-66

Author(s):

Dong Nie ◽

Zheng Yan ◽

Nan Zhao ◽

Tingshao Zhu

Keyword(s):

Social Network ◽

Pilot Study ◽

Survey Data ◽

Real World ◽

Social Communication ◽

Sina Weibo ◽

Only Children ◽

Daily Behavior ◽

The Social ◽

Network Platform

Extensive research reported that only children (“Onlies”) have different daily behavior from children with siblings (“Others”) in the real world. However, little is known about whether Onlies and Others behave differently in the cyber world, especially on the social network. A pilot study has been conducted to compare the behaviors of Onlies and Others on Sina Weibo, a leading social network platform in China. Through analyzing both online Weibo data and survey data from 1792 Weibo users (52% Onlies), several differences between Onlies' and Others' Weibo behaviors were found: Onlies tended to be more willing to express themselves and be more active in social communication within a smaller social circle than Others. More explorations should be done to fully understand these differences between the two groups.

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International Journal of Technology and Human Interaction ◽

10.4018/ijthi.2013100102 ◽

2013 ◽

Vol 9 (4) ◽

pp. 20-40 ◽

Cited By ~ 2

Author(s):

Franklin N. A. Yartey ◽

Louisa Ha

Keyword(s):

College Students ◽

Social Media ◽

Survey Data ◽

Network Externalities ◽

Public University ◽

Smart Phones ◽

Social Implications ◽

The Social ◽

Use Of Social Media ◽

Point To Point

In this study, the authors examine the use of smart phones for self-broadcasting among college students based on motivation and network externalities theories. The authors propose that smartphones have changed telephones from a point-to-point interpersonal medium to a broadcast medium for individuals to disseminate information to their networks through the use of social media. The authors hypothesized that the more friends and followers a student has on Facebook and Twitter respectively, the more likely the student will use friends and followers as self-broadcasting mediums from their smartphones. The hypothesis was supported based on survey data collected at a public university. The study also discusses the social implications of using smartphones as a broadcast and self-promotion medium.

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Crime Victims and their Social Network: A Field Study on the Cognitive Effects of Victimisation, Attributional Responses and the Victim-Blaming Model

International Review of Victimology ◽

10.1177/026975809500300404 ◽

1995 ◽

Vol 3 (4) ◽

pp. 309-322 ◽

Cited By ~ 8

Author(s):

Frans Willem Winkel ◽

Adriaan Denkers

Keyword(s):

Social Network ◽

Field Study ◽

Negative Impact ◽

Self Control ◽

Victim Blaming ◽

Cognitive Effects ◽

Dominant Position ◽

Future Studies ◽

The Social ◽

And Control

A field study is reported focusing on the cognitive effects of criminal victimisation, on the types of responses victims encounter in their social network, and on the validity of the ‘victim blaming model’. Data reveal that victimisations have a negative impact on the perceived benevolence of the world. Perceptions of self control and control over outcomes are reduced, and victims consider themselves less as persons having luck in life. These cognitive effects appear to stretch out beyond those directly involved. Results generally do not support the theoretically dominant position in the victimological literature on ‘blaming the victim’. Empathical responses and external attributions from the social network are much more common than internal responses to victimisation. Moreover, internal attributions from the social network appear to work more positively on the wellbeing of victims than external attributions. These outcomes - which are in line with the Janoff-Bulman model - are clearly in contrast to the ‘victim blaming model’. Some implications for future studies are discussed.

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Digital Arts and Entertainment ◽

10.4018/978-1-4666-6114-1.ch006 ◽

2014 ◽

pp. 126-148

Author(s):

Franklin N. A. Yartey ◽

Louisa Ha

Keyword(s):

College Students ◽

Social Media ◽

Survey Data ◽

Network Externalities ◽

Public University ◽

Smart Phones ◽

Social Implications ◽

The Social ◽

Use Of Social Media ◽

Point To Point

In this study, the authors examine the use of smart phones for self-broadcasting among college students based on motivation and network externalities theories. The authors propose that smartphones have changed telephones from a point-to-point interpersonal medium to a broadcast medium for individuals to disseminate information to their networks through the use of social media. The authors hypothesized that the more friends and followers a student has on Facebook and Twitter respectively, the more likely the student will use friends and followers as self-broadcasting mediums from their smartphones. The hypothesis was supported based on survey data collected at a public university. The study also discusses the social implications of using smartphones as a broadcast and self-promotion medium.

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The social network

Skin & Allergy News ◽

10.1016/s0037-6337(13)70045-7 ◽

2013 ◽

Vol 44 (2) ◽

pp. 22

Author(s):

ALAN ROCKOFF

Keyword(s):

Social Network ◽

The Social

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The Multilevel p2 Model

Methodology ◽

10.1027/1614-2241.2.1.42 ◽

2006 ◽

Vol 2 (1) ◽

pp. 42-47 ◽

Cited By ~ 47

Author(s):

Bonne J. H. Zijlstra ◽

Marijtje A. J. van Duijn ◽

Tom A. B. Snijders

Keyword(s):

Social Network ◽

Network Data ◽

Mcmc Algorithm ◽

Independent Observation ◽

Single Observation ◽

Multiple Networks ◽

Social Network Data ◽

Multiple Observations ◽

Practical Support ◽

The Social

The p 2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p 2 model is proposed for the case of multiple observations of social networks, for example, in a sample of schools. The multilevel p 2 model defines an identical p 2 model for each independent observation of the social network, where parameters are allowed to vary across the multiple networks. The multilevel p 2 model is estimated with a Bayesian Markov Chain Monte Carlo (MCMC) algorithm that was implemented in free software for the statistical analysis of complete social network data, called StOCNET. The new model is illustrated with a study on the received practical support by Dutch high school pupils of different ethnic backgrounds.

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ПРАГМАТИЧНИЙ ПОТЕНЦІАЛ НАТИВНОЇ РЕКЛАМИ: ФОРМИ, ТРЕНДИ (НА ПРИКЛАДІ НАТИВНОГО КОНТЕНТУ В СОЦІАЛЬНІЙ МЕРЕЖІ FACEBOOK ЩОДО БРЕНДА ФАКУЛЬТЕТУ ЖУРНАЛІСТИКИ ЗНУ)

State and Regions. Series: Social Communications ◽

10.32840/cpu2219-8741/2020.1(41).18 ◽

2020 ◽

pp. 113

Author(s):

V. Kovpak ◽

N. Trotsenko

Keyword(s):

Social Network ◽

Professional Training ◽

Educational Process ◽

Communication Strategy ◽

Student Centered ◽

Teacher Student ◽

The Social ◽

National University ◽

High Level ◽

The Impact

<div>The article analyzes the peculiarities of the format of native advertising in the media space, its pragmatic potential (in particular, on the example of native content in the social network Facebook by the brand of the journalism department of ZNU), highlights the types and trends of native advertising. The following research methods were used to achieve the purpose of intelligence: descriptive (content content, including various examples), comparative (content presentation options) and typological (types, trends of native advertising, in particular, cross-media as an opportunity to submit content in different formats (video, audio, photos, text, infographics, etc.)), content analysis method using Internet services (using Popsters service). And the native code for analytics was the page of the journalism department of Zaporizhzhya National University on the social network Facebook. After all, the brand of the journalism department of Zaporozhye National University in 2019 celebrates its 15th anniversary. The brand vector is its value component and professional training with balanced distribution of theoretical and practical blocks (seven practices), student-centered (democratic interaction and high-level teacher-student dialogue) and integration into Ukrainian and world educational process (participation in grant programs).</div>And advertising on social networks is also a kind of native content, which does not appear in special blocks, and is organically inscribed on one page or another and unobtrusively offers, just remembering the product as if «to the word». Popsters service functionality, which evaluates an account (or linked accounts of one person) for 35 parameters, but the main three areas: reach or influence, or how many users evaluate, comment on the recording; true reach – the number of people affected; network score – an assessment of the audience’s response to the impact, or how far the network information diverges (how many share information on this page).Key words: nativeness, native advertising, branded content, special project, communication strategy.

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