scholarly journals Recommending Links to Maximize the Influence in Social Networks

2019 ◽  
Author(s):  
Federico Corò ◽  
Gianlorenzo D'Angelo ◽  
Yllka Velaj
Keyword(s):  
Social Media ◽  
Social Influence ◽  
Fixed Number ◽  
Constant Factor ◽  
Computational Time ◽  
Recommendation Algorithm ◽  
The Social ◽  
Social Link ◽  
Social Biases ◽  
Link Recommendation

Social link recommendation systems, like "People-you-may-know" on Facebook, "Who-to-follow" on Twitter, and "Suggested-Accounts" on Instagram assist the users of a social network in establishing new connections with other users. While these systems are becoming more and more important in the growth of social media, they tend to increase the popularity of users that are already popular. Indeed, since link recommenders aim at predicting users' behavior, they accelerate the creation of links that are likely to be created in the future, and, as a consequence, they reinforce social biases by suggesting few (popular) users, while giving few chances to the majority of users to build new connections and increase their popularity.In this paper we measure the popularity of a user by means of its social influence, which is its capability to influence other users' opinions, and we propose a link recommendation algorithm that evaluates the links to suggest according to their increment in social influence instead of their likelihood of being created. In detail, we give a constant factor approximation algorithm for the problem of maximizing the social influence of a given set of target users by suggesting a fixed number of new connections. We experimentally show that, with few new links and small computational time, our algorithm is able to increase by far the social influence of the target users. We compare our algorithm with several baselines and show that it is the most effective one in terms of increased influence.

Link Recommendation for Social Influence Maximization

2021 ◽  
Vol 15 (6) ◽  
pp. 1-23
Author(s):  
Federico Coró ◽  
Gianlorenzo D’angelo ◽  
Yllka Velaj
Keyword(s):  
Social Influence ◽  
User Behavior ◽  
Threshold Model ◽  
Fixed Number ◽  
Computational Time ◽  
Social Bias ◽  
Linear Threshold ◽  
The Social ◽  
Social Link ◽  
Link Recommendation

Social link recommendation systems, like “People-you-may-know” on Facebook, “Who-to-follow” on Twitter, and “Suggested-Accounts” on Instagram assist the users of a social network in establishing new connections with other users. While these systems are becoming more and more important in the growth of social media, they tend to increase the popularity of users that are already popular. Indeed, since link recommenders aim to predict user behavior, they accelerate the creation of links that are likely to be created in the future and, consequently, reinforce social bias by suggesting few (popular) users, giving few chances to most users to create new connections and increase their popularity. In this article, we measure the popularity of a user by means of her social influence, which is her capability to influence other users’ opinions, and we propose a link recommendation algorithm that evaluates the links to suggest according to their increment in social influence instead of their likelihood of being created. In detail, we give a factor approximation algorithm for the problem of maximizing the social influence of a given set of target users by suggesting a fixed number of new connections considering the Linear Threshold model as model for diffusion. We experimentally show that, with few new links and small computational time, our algorithm is able to increase by far the social influence of the target users. We compare our algorithm with several baselines and show that it is the most effective one in terms of increased influence.

scholarly journals What Drives Continuance Intention towards Social Media? Social Influence and Identity Perspectives

2020 ◽  
Vol 12 (17) ◽  
pp. 7081 ◽  
Author(s):  
Athapol Ruangkanjanases ◽  
Shu-Ling Hsu ◽  
Yenchun Jim Wu ◽  
Shih-Chih Chen ◽  
Jo-Yu Chang
Keyword(s):  
Social Media ◽  
Social Identity ◽  
New Media ◽  
Social Influence ◽  
Perceived Usefulness ◽  
Continuance Intention ◽  
Positive Effects ◽  
The Social ◽  
Media Platform ◽  
Continuous Usage Intention

With the growth of social media communities, people now use this new media to engage in many interrelated activities. As a result, social media communities have grown into popular and interactive platforms among users, consumers and enterprises. In the social media era of high competition, increasing continuance intention towards a specific social media platform could transfer extra benefits to such virtual groups. Based on the expectation-confirmation model (ECM), this research proposed a conceptual framework incorporating social influence and social identity as key determinants of social media continuous usage intention. The research findings of this study highlight that: (1) the social influence view of the group norms and image significantly affects social identity; (2) social identity significantly affects perceived usefulness and confirmation; (3) confirmation has a significant impact on perceived usefulness and satisfaction; (4) perceived usefulness and satisfaction have positive effects on usage continuance intention. The results of this study can serve as a guide to better understand the reasons for and implications of social media usage and adoption.

scholarly journals Motives to engage with sports brands on Facebook and Instagram–The case of a Portuguese football club

2020 ◽  
Vol 21 (2) ◽  
pp. 325-349
Author(s):  
Joana César Machado ◽  
Carla Carvalho Martins ◽  
Frederico Correia Ferreira ◽  
Susana Costa e Silva ◽  
Paulo Alexandre Duarte
Keyword(s):  
Social Media ◽  
Social Influence ◽  
Online Survey ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Content Type ◽  
Content Consumption ◽  
The Social ◽  
Marketing Activities ◽  
The Impact

PurposeSocial network sites are key marketing tools that allow brands to connect and engage with consumers. However, there is still a lack of evidence of their value for football brands. This research aims to understand the motivations for fans to engage with their favourite football brands on Facebook and Instagram.Design/methodology/approachAn online survey was performed, resulting in 214 valid responses. As the social media strategy followed by the football brand analysed was built around games, the authors divided fans into two groups based on the main method in which the club's games are watched: in stadium versus mediated. Multiple linear regression analysis was used to explore the relationship between motivations and fans' engagement, through content consumption and contribution, on Facebook and Instagram. Analysis was performed first with the whole sample and then by group (stadium attendance vs mediated attendance fans).FindingsThe findings show that social influence, entertainment, searching for information and rewards are the most relevant motivations for consumers to engage with brand-related content on Facebook. Entertainment, rewards and social influence are the main motivations influencing consumer interactions on Instagram. Group moderation was only confirmed in the impact of social influence on Facebook page content consumption.Originality/valueThe results provide valuable insights into the social media marketing activities of sports brands, which will assist brand managers to develop strategies for effectively stimulating engagement with the different groups of fans.

The Social Experience of Entertainment Media

2011 ◽  
Vol 23 (3) ◽  
pp. 111-121 ◽  
Author(s):  
Randi Shedlosky-Shoemaker ◽  
Kristi A. Costabile ◽  
Haylee K. DeLuca ◽  
Robert M. Arkin
Keyword(s):  
Social Media ◽  
Social Influence ◽  
Social Experience ◽  
Current Work ◽  
Entertainment Media ◽  
Future Directions ◽  
Peer Evaluations ◽  
The Social

People often look to others for guidance when selecting narrative entertainment. Previous work has demonstrated that this social guidance forms the basis of people’s expectations and subsequently affects people’s experience. The current work extends previous research by exploring the influence of peer evaluations of a story, on enjoyment of and psychological transportation in the written narrative. In two experiments, participants read peer evaluations prior to reading the story. Results of Experiment 1 revealed that social influence guides readers’ expectations, attention to elements in the narrative, reported enjoyment, and feelings of transportation in the narrative. This influence was particularly apparent when readers were given unfavorable reviews of the stimulus. In the second experiment, readers were given peer evaluations that were either confirmed or disconfirmed by other readers. Results indicated that valence of peer evaluations influenced both transportation and enjoyment. Additionally, inconsistent evaluations increased feelings of transportation, but consistency alone had no effect on reported enjoyment. Implications for social media experiences and future directions in research on entertainment media are discussed.

scholarly journals Unveiling Social Gratifications Sought and Obtained from Social Media Utilization

2020 ◽  
Vol 12 (2) ◽  
pp. 168
Author(s):  
Ridwan Adetunji Raji ◽  
Olawale Abdulgaffar Arikewuyo ◽  
Adeyemo Saheed Oladimeji Adeyemi ◽  
Muhammad Ramzan Pahore
Keyword(s):  
Social Capital ◽  
Social Media ◽  
Social Influence ◽  
Social Interactions ◽  
Online Survey ◽  
Bridging Social Capital ◽  
The Social ◽  
Networking Tool ◽  
Bonding And Bridging ◽  
Social Gratification

<p class="Default"><em>Going by the proposition of the Uses and Gratifications Theory (UGT), people are motivated to use media by various psychological factors and for obtaining different forms of gratifications. However, as social media continue to play an essential role in shaping the sociability and bridging social connectivity and interactions among its users, therefore, this study seeks to incorporate social influence and social interactions as the social gratification sought in social media utilization, as well as both bonding and bridging social capital as social gratification obtained from social media utilization. An online survey was conducted among 400 users of Instagram </em><em>in Nigeria. </em><em>The data analyzed with PLS-SEM revealed that social influence and social interaction significantly motivate social media utilization. Also, social media utilization is significantly associated with bonding and bridging social capital. Impliedly, this study shows that social media is a social and networking tool which is stimulated by social factors and for achieving social purposes such as getting help, support and community engagements.</em></p>

scholarly journals Exploring the Relationship Between Social Media and Social Influence

2021 ◽  
pp. 934-953
Author(s):  
Ali Usman ◽  
Sebastian Okafor
Keyword(s):  
Social Media ◽  
Social Influence ◽  
Purchase Intentions ◽  
Online Marketing ◽  
Media Impact ◽  
Making Sense ◽  
Complex Interactions ◽  
Online Brand Communities ◽  
The Social ◽  
The Relationship

Online behavioral tailoring has become an integral part of online marketing strategies. Contemporary marketers increasingly seek to create an influential environment on social media to empower online users to participate in online brand communities. By interacting in this way, online communities hosted by brands marketers can enhance the nature of the complex interactions that occur amongst those that participate. Such online interactions lead to three different types of social influence compliance, internalization, and identity, which develop the consumers' purchase intentions. This chapter explains how the social influence support the change in beliefs, attitude, and intentions of the online consumers in the user-generated social media networking sites (SNSs). Furthermore, it discusses the functional impact of such online social influence that enables companies to understand the perceptions and needs of online users making sense of how multiple levels of social influence phenomenon on social media impact on consumers purchase intentions.

scholarly journals The Network Visibility Problem

2022 ◽  
Vol 40 (2) ◽  
pp. 1-42
Author(s):  
Khashayar Gatmiry ◽  
Manuel Gomez-Rodriguez
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Greedy Algorithm ◽  
Real Data ◽  
Recommendation Algorithm ◽  
Attention Economy ◽  
Set Function ◽  
Link Recommendation ◽  
The Greedy Algorithm

Social media is an attention economy where broadcasters are constantly competing for attention in their followers’ feeds. Broadcasters are likely to elicit greater attention from their followers if their posts remain visible at the top of their followers’ feeds for a longer period of time. However, this depends on the rate at which their followers receive information in their feeds, which in turn depends on the broadcasters they follow. Motivated by this observation and recent calls for fairness of exposure in social networks, in this article, we look at the task of recommending links from the perspective of visibility optimization. Given a set of candidate links provided by a link recommendation algorithm, our goal is to find a subset of those links that would provide the highest visibility to a set of broadcasters. To this end, we first show that this problem reduces to maximizing a nonsubmodular nondecreasing set function under matroid constraints. Then, we show that the set function satisfies a notion of approximate submodularity that allows the standard greedy algorithm to enjoy theoretical guarantees. Experiments on both synthetic and real data gathered from Twitter show that the greedy algorithm is able to consistently outperform several competitive baselines.

The Future of Social Influence in Social Psychology

2016 ◽  
Author(s):  
Stephen G. Harkins ◽  
Kipling D. Williams
Keyword(s):  
Social Psychology ◽  
Social Media ◽  
Social Influence ◽  
Original Research ◽  
Face To Face ◽  
The Social ◽  
The Future

With notable exceptions, social influence has not played a major role in social psychology since the mid-1980s. The chapters in this volume, along with other developments, set the stage for a return of social influence to its once preeminent position. The chapters contribute to the renaissance of interest in social influence in a variety of ways. Some chapters show us that it is time to re-examine classic topics in the context of what has been learned since the original research was conducted. Others show how integrations/elaborations that advance our understanding of social influence processes are now possible. The chapters also reveal lacunae in the social influence literature, and suggest future lines of research. Perhaps the most important of these will take into account the change from traditional social influence that occurs face-to-face to social media-mediated influence that is likely to characterize many of our interactions in the future.

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