Survey of Emotion Influence in Image Social Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 68
Author(s):  
Y. Helan Mettilda ◽  
R. Anbuselvi
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Basic Mechanism ◽  
Opinion Leaders ◽  
Interesting Problem ◽  
Structural Holes ◽  
Psychological Theories ◽  
The Social ◽  
The Status

Psychological theories propose that emotion represents the status of mind and natural responses of one’s cognitive system. Emotions are a difficult state of feeling that results in physical and psychological changes that power our actions. In this paper, we study an interesting problem of emotion infection in social networks.  In this paper, we study a different interesting problem of emotion influence in social networks. In particular, by employing an image social network as the basis of our study, we try to unveil how users’ emotional statuses influence each other and how users’ positions in the social network affect their influential strength on emotion in different papers.  We also find out several interesting phenomena. For example, the possibility that a user feels happy is about linear to the number of friends who are also happy; but taking a nearer look, the pleasure chance is super linear to the number of happy friends who act as opinion leaders in the network and sub linear in the number of happy friends who span structural holes. This offers a new chance to understand the basic mechanism of emotional contagion in online social networks.

Multilevel Visualization Using Enhanced Social Network Analysis with Smartphone Data

2013 ◽  
Vol 5 (4) ◽  
pp. 34-54 ◽  
Author(s):  
Panagiotis Andriotis ◽  
Zacharias Tzermias ◽  
Anthi Mparmpaki ◽  
Sotiris Ioannidis ◽  
George Oikonomou
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Direct Marketing ◽  
Forensic Analysis ◽  
Three Dimensions ◽  
Fully Integrated ◽  
Aggregate Information ◽  
The Social ◽  
Correlated Information

While technology matures and becomes more productive, mobile devices can be affordable and, consequently, fully integrated in people's lives. After their unexpected bloom and acceptance, Online Social Networks are now sources of valuable information. The authors therefore use them for tasks varying from direct marketing to forensic analysis. The authors have already seen Social Network Forensics techniques focused on particular networks implementing methods that collect data from user accounts. During the forensic analysis it is common to aggregate information from different sources but, usually, this procedure causes correlation problems. Here, the authors present their method to correlate data gathered from various social networks in combination with smartphones creating a new form of social map of the user under investigation. In addition, the authors introduce a multi level graph that utilises the correlated information from the smartphone and the social networks and demonstrates in three dimensions the relevance of each contact with the suspect.

Building Online Social Networks to Engage Female Students in Information Systems

2015 ◽  
Vol 10 (4) ◽  
pp. 33-51
Author(s):  
Jaymeen R. Shah ◽  
Hsun-Ming Lee
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Information Systems ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Role Models ◽  
Online Social Network ◽  
Research Process ◽  
Female Students ◽  
The Social

During the next decade, enrollment growth in Information Systems (IS) related majors is unlikely to meet the predicted demand for qualified IS graduates. Gender imbalance in the IS related program makes the situation worse as enrollment and retention of women in the IS major has been proportionately low compared to male. In recent years, majority of high school and college students have integrated social networking sites in their daily life and habitually use these sites. Providing female students access to role models via an online social network may enhance their motivation to continue as an IS major and pursue a career in IS field. For this study, the authors follow the action research process – exploration of information systems development. In particular, a Facebook application was developed to build the social network connecting role models and students. Using the application, a basic framework is tested based on the gender of participants. The results suggest that it is necessary to have adequate number of role models accessible to students as female role-models tend to select fewer students to develop relationships with a preference for female students. Female students likely prefer composite role models from a variety of sources. This pilot study yields valuable lessons to provide informal learning fostered by role modeling via online social networks. The Facebook application may be further expanded to enhance female students' interests in IS related careers.

The Alt-social Network of Natalie Bookchin’s Testament

2016 ◽  
Vol 18 (5) ◽  
pp. 459-477
Author(s):  
Sarah Whitcomb Laiola
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Social Web ◽  
User Interactions ◽  
Media Criticism ◽  
Direct Translation ◽  
The Social

This article addresses issues of user precarity and vulnerability in online social networks. As social media criticism by Jose van Dijck, Felix Stalder, and Geert Lovink describes, the social web is a predatory system that exploits users’ desires for connection. Although accurate, this critical description casts the social web as a zone where users are always already disempowered, so fails to imagine possibilities for users beyond this paradigm. This article examines Natalie Bookchin’s composite video series, Testament, as it mobilizes an alt-(ernative) social network of vernacular video on YouTube. In the first place, the alt-social network works as an iteration of “tactical media” to critically reimagine empowered user-to-user interactions on the social web. In the second place, it obfuscates YouTube’s data-mining functionality, so allows users to socialize online in a way that evades their direct translation into data and the exploitation of their social labor.

How Social Networks Shape Social Comparison

2019 ◽  
pp. 443-461
Author(s):  
Jingwen Zhang ◽  
Damon Centola
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Comparison ◽  
Online Social Networks ◽  
Experimental Studies ◽  
Social Perceptions ◽  
Negative Consequences ◽  
Online Networks ◽  
Comparison Research ◽  
The Social

While social comparison research has focused on the processes and consequences of how the comparer gleans information from the comparison other (individual or group), recent research on social networks demonstrates how information and influence are distributed across persons in a network. This chapter reviews social influence processes in social networks. The authors first review recent research on social comparison and its negative consequences in online social networks. Then the authors delve into discussing the social network causes of biased social perceptions online and how this can be remedied by building more accurate perceptions through constructed online networks. Lastly, the authors discuss findings from recent experimental studies that illustrate how constructed online networks can harness social comparison to induce significant changes in health behavior.

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.

Do I Deserve to Spend? Online Social Support and Spending Pleasure

2020 ◽  
pp. 193896552097357
Author(s):  
Kawon Kim ◽  
Melissa A. Baker
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Social Network ◽  
Boundary Conditions ◽  
Online Social Networks ◽  
Service Industry ◽  
Online Social Network ◽  
Online Social Support ◽  
The Social ◽  
Influence Perceptions

Despite evidence of people posting their consumption experiences to online social networks to fulfill the needs of social support, an understanding of how online social support affects post-consumption spending behaviors remains elusive. This research aims to examine how online social support from online social network friends and the firm influence perceptions of self-deservingness and spending pleasure. Across two studies, this research provides evidence that social support gained through online social networks influences consumers’ spending pleasure through perceptions of their own deservingness. Notably, this study reveals that people obtain social support in online social networks from two sources: social networks friends and firms through receiving “Likes” and “Comments” on their post. This study also explores boundary conditions for when online social support is more effective on spending pleasure. The findings not only broaden the social support literature but also address the benefit to the service industry by understanding how social support can enhance spending pleasure.

The conquest of vitalism or the eclipse of organicism? The 1930s Cambridge organizer project and the social network of mid-twentieth-century biology

2013 ◽  
Vol 47 (2) ◽  
pp. 281-304 ◽  
Author(s):  
ERIK PETERSON
Keyword(s):  
Social Networks ◽  
Twentieth Century ◽  
Social Network ◽  
Theoretical Biology ◽  
Limited Evidence ◽  
Micro Scale ◽  
The Social ◽  
Macro Scale ◽  
The Status ◽  
History Of

AbstractIn the 1930s, two concepts excited the European biological community: the organizer phenomenon and organicism. This essay examines the history of and connection between these two phenomena in order to address the conventional ‘rise-and-fall’ narrative that historians have assigned to each. Scholars promoted the ‘rise-and-fall’ narrative in connection with a broader account of the devitalizing of biology through the twentieth century. I argue that while limited evidence exists for the ‘fall of the organizer concept’ by the 1950s, the organicism that often motivated the organizer work had no concomitant fall – even during the mid-century heyday of molecular biology. My argument is based on an examination of shifting social networks of life scientists from the 1920s to the 1970s, many of whom attended or corresponded with members of the Cambridge Theoretical Biology Club (1932–1938). I conclude that the status and cohesion of these social networks at the micro scale was at least as important as macro-scale conceptual factors in determining the relative persuasiveness of organicist philosophy.

Social Networks, the Tertius Iungens Orientation, and Involvement in Innovation

2005 ◽  
Vol 50 (1) ◽  
pp. 100-130 ◽  
Author(s):  
David Obstfeld
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Skill ◽  
Organizational Innovation ◽  
Strategic Orientation ◽  
Social Knowledge ◽  
Structural Holes ◽  
Automotive Manufacturer ◽  
The Social ◽  
Behavioral Orientation

This study examines the microprocesses in the social networks of those involved in organizational innovation and their strategic behavioral orientation toward connecting people in their social network by either introducing disconnected individuals or facilitating new coordination between connected individuals. This tertius iungens (or “third who joins”) strategic orientation, contrasts with the tertius gaudens orientation emphasized in structural holes theory, which concerns the advantage of a broker who can play people off against one another for his or her own benefit. Results of a multimethod study of networks and innovation in an engineering division of an automotive manufacturer show that a tertius iungens orientation, dense social networks, and diverse social knowledge predict involvement in innovation. Implications of the study for innovation and social networks, as well as for social skill and agency within firms are presented.

Taxonomy of Influence Maximization Techniques in Unknown Social Networks

2021 ◽  
pp. 351-363
Author(s):  
B. Bazeer Ahamed ◽  
Sudhakaran Periakaruppan
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Graph Mining ◽  
Influence Maximization ◽  
Business Strategies ◽  
The Social ◽  
Spread Of Influence ◽  
Maximization Algorithms ◽  
Real Challenge

Influence maximization in online social networks (OSNs) is the problem of discovering few nodes or users in the social network termed as ‘seed nodes', which can help the spread of influence in the network. With the tremendous growth in social networking, the influence exerted by users of a social network on other online users has caught the attention of researchers to develop effective influence maximization algorithms to be applied in the field of business strategies. The main application of influence maximization is promoting the product to a set of users. However, a real challenge in influence maximization algorithms to deal with enormous amount of users or nodes obtainable in any OSN is posed. The authors focused on graph mining of OSNs for generating ‘seed sets' using standard influence maximization techniques. Many standard influence maximization models are used for calculation of spread of influence; a novel influence maximization technique, namely the DegGreedy technique, has been illustrated along with experimental results to make a comparative analysis of the existing techniques.

scholarly journals A Methodology for Evaluating Algorithms That Calculate Social Influence in Complex Social Networks

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-20
Author(s):  
Vanja Smailovic ◽  
Vedran Podobnik ◽  
Ignac Lovrek
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Social Influence ◽  
Online Social Networks ◽  
Ground Truth ◽  
Descriptive Statistics ◽  
The Social ◽  
Alternative Approaches

Online social networks are complex systems often involving millions or even billions of users. Understanding the dynamics of a social network requires analysing characteristics of the network (in its entirety) and the users (as individuals). This paper focuses on calculating user’s social influence, which depends on (i) the user’s positioning in the social network and (ii) interactions between the user and all other users in the social network. Given that data on all users in the social network is required to calculate social influence, something not applicable for today’s social networks, alternative approaches relying on a limited set of data on users are necessary. However, these approaches introduce uncertainty in calculating (i.e., predicting) the value of social influence. Hence, a methodology is proposed for evaluating algorithms that calculate social influence in complex social networks; this is done by identifying the most accurate and precise algorithm. The proposed methodology extends the traditional ground truth approach, often used in descriptive statistics and machine learning. Use of the proposed methodology is demonstrated using a case study incorporating four algorithms for calculating a user’s social influence.

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