Social link recommendation by learning hidden topics

2011 ◽  
Author(s):  
Masoud Makrehchi
Keyword(s):  
Social Link ◽  
Link Recommendation

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 Teachers and Interpersonal Relationships: a Question of Distance and Social Link?

K@iros ◽  
2019 ◽  
Author(s):  
Tony ORIVAL ◽  
Keyword(s):  
Secondary School ◽  
Interpersonal Relationships ◽  
Social Distance ◽  
Oral Language ◽  
Secondary School Teachers ◽  
Language Practices ◽  
School Teachers ◽  
The Social ◽  
Social Link

Social distance and social link are important in the relationships between teachers and pupils. This question deserves to be examined with a sociological eye. The aim of this book chapter is to clarify the meaning of the terms (“social distance” and “social link”) and to analyze the influences of the social distance reconfigurations on the behavior of the first towards the second. Based on interviews with secondary school teachers, this chapter aims to show how do the influences of social distance reconfigurations change or not their oral language practices.

scholarly journals The society of the debacle: Triptych of the discourse of the university

2010 ◽  
Vol 21 (2) ◽  
pp. 117-142
Author(s):  
Nikola Janovic
Keyword(s):  
Everyday Life ◽  
Social Economy ◽  
Good Alternative ◽  
Global Crisis ◽  
Social Link ◽  
The University

The main intention of this text is to present three inter-connected projections of the current global crisis of the postmodern capitalism: discursive, sociological and cultural/political. Discursive projection is considering the crisis of the postmodern capitalism through the perspective of the discursive paradigmatic restructuring (social link), sociological projection is giving interpretation of the postmodern social economy paradigm (society of knowledge), whilst the cultural/political projection is discussing the postmodern ideological forms of everyday life (cultural capitalism). In the last instance, all three are raising a question: Is there any good alternative?

Sign in / Sign up

Export Citation Format

Share Document