Motivational factors of information exchange in social information spaces

2014 ◽  
Vol 36 ◽  
pp. 549-558 ◽  
Author(s):  
Christina Matschke ◽  
Johannes Moskaliuk ◽  
Franziska Bokhorst ◽  
Till Schümmer ◽  
Ulrike Cress
Keyword(s):  
Information Exchange ◽  
Social Information ◽  
Motivational Factors ◽  
Information Spaces

scholarly journals Vicarious reward unblocks associative learning about novel cues in male rats

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Sander van Gurp ◽  
Jochen Hoog ◽  
Tobias Kalenscher ◽  
Marijn van Wingerden
Keyword(s):  
Social Learning ◽  
Associative Learning ◽  
Information Exchange ◽  
Social Information ◽  
Secondary Reinforcement ◽  
Male Rats ◽  
Social Signals ◽  
Reward Delivery ◽  
Vicarious Reward

Many species, including rats, are sensitive to social signals and their valuation is important in social learning. Here we introduce a task that investigates if mutual reward delivery in male rats can drive associative learning. We found that when actor rats have fully learned a stimulus-self-reward association, adding a cue that predicted additional reward to a partner unblocked associative learning about this cue. By contrast, additional cues that did not predict partner reward remained blocked from acquiring positive associative value. Importantly, this social unblocking effect was still present when controlling for secondary reinforcement but absent when social information exchange was impeded, when mutual reward outcomes were disadvantageously unequal to the actor or when the added cue predicted reward delivery to an empty chamber. Taken together, these results suggest that mutual rewards can drive associative learning in rats and is dependent on vicariously experienced social and food-related cues.

Improving Personal and Social Information Management with Advanced Tagging

2013 ◽  
Author(s):  
Vanesa Mirzaee ◽  
Maryam Najafian Razavi ◽  
Lee Iverson
Keyword(s):  
Web 2.0 ◽  
Information Management ◽  
Personal Information ◽  
Social Information ◽  
Personal Information Management ◽  
Information Spaces ◽  
Management Application

This paper describes an innovative tagging model incorporated into a web 2.0 social and personal information management application. Our work utilizes web 2.0 tagging concepts in a new way in an effort to provide better support for users’ needs for contextualization and personalization of their information spaces for both personal…Cet article décrit un modèle innovateur d’étiquetage intégré à une application de gestion de l’information personnelle et sociale du Web 2.0. Notre travail utilise les concepts de l’étiquetage du Web 2.0 d’une manière nouvelle, afin de mieux subvenir aux besoins des utilisateurs pour la contextualisation et la personnalisation de leurs espaces informationnels, pour des fins personnelles… 

scholarly journals Social Information Exchange in Aitys Performances

2014 ◽  
Vol 122 ◽  
pp. 72-76
Author(s):  
Madiyar Saudbayev ◽  
Berdak Bayimbetov ◽  
Bauyrzhan Karipov
Keyword(s):  
Information Exchange ◽  
Social Information

scholarly journals The wisdom of partisan crowds

2019 ◽  
Vol 116 (22) ◽  
pp. 10717-10722 ◽  
Author(s):  
Joshua Becker ◽  
Ethan Porter ◽  
Damon Centola
Keyword(s):  
Social Information Processing ◽  
Information Exchange ◽  
Collective Intelligence ◽  
Social Information ◽  
Political Polarization ◽  
Primary Concern ◽  
Wisdom Of Crowds ◽  
Partisan Bias ◽  
Before And After ◽  
The Wisdom Of Crowds

Theories in favor of deliberative democracy are based on the premise that social information processing can improve group beliefs. While research on the “wisdom of crowds” has found that information exchange can increase belief accuracy on noncontroversial factual matters, theories of political polarization imply that groups will become more extreme—and less accurate—when beliefs are motivated by partisan political bias. A primary concern is that partisan biases are associated not only with more extreme beliefs, but also with a diminished response to social information. While bipartisan networks containing both Democrats and Republicans are expected to promote accurate belief formation, politically homogeneous networks are expected to amplify partisan bias and reduce belief accuracy. To test whether the wisdom of crowds is robust to partisan bias, we conducted two web-based experiments in which individuals answered factual questions known to elicit partisan bias before and after observing the estimates of peers in a politically homogeneous social network. In contrast to polarization theories, we found that social information exchange in homogeneous networks not only increased accuracy but also reduced polarization. Our results help generalize collective intelligence research to political domains.

From PageRank to Social Rank

2011 ◽  
pp. 134-154
Author(s):  
Sebastian Marius Kirsch ◽  
Melanie Gnasa ◽  
Markus Won ◽  
Armin Cremers
Keyword(s):  
Social Networks ◽  
Information Retrieval ◽  
Social Network ◽  
Social Information ◽  
Social Rank ◽  
Statistical Properties ◽  
Retrieval Algorithm ◽  
Information Spaces ◽  
The Social

Social information spaces are characterized by the presence of a social network between participants. This chapter presents methods for utilizing social networks for information retrieval, by applying graph authority measures to the social network. We show how to integrate authority measures in an information retrieval algorithm. In order to determine the suitability of the described algorithms, we examine the structure and statistical properties of social networks, and present examples of social networks as well as evaluation results.

Motivational Factors of Information Exchange Questionnaire

2014 ◽  
Author(s):  
Christina Matschke ◽  
Johannes Moskaliuk ◽  
Franziska Bokhorst ◽  
Till Schümmer ◽  
Ulrike Cress
Keyword(s):  
Information Exchange ◽  
Motivational Factors
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