Mechanisms for individual, group-based and crowd-based attention to social information

被引:0
|
作者
Jelena Ristic
Francesca Capozzi
机构
[1] McGill University,Department of Psychology
[2] Université du Québec à Montréal,Department of Psychology
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Two or more interacting individuals make up a social group. In this Review, we show that human attention plays a key part in the selection, management and maintenance of social interactions between individual members of social groups of any size. Three attentional mechanisms are presented here. The individual cue-selection mechanism facilitates the selection of social cues, such as gaze, facial or head information, from individual group members. The group-based selection mechanism enables selection based on the perceived quality of social cues derived from individual group members or the emerging interactions between individual group members. Finally, the crowd-based selection mechanism enables selection based on an overall representation of the social information derived from assessing the majority of consistent cues in the crowd. The three attentional mechanisms are used flexibly, interchangeably and dynamically as a function of group size and the ability to individuate group members.
引用
收藏
页码:721 / 732
页数:11
相关论文
共 50 条
  • [21] Crowd-based peer review passes test
    Ritter, Steve
    [J]. CHEMICAL & ENGINEERING NEWS, 2017, 95 (24) : 7 - 7
  • [22] QualityCrowd - A Framework for Crowd-based Quality Evaluation
    Keimel, Christian
    Habigt, Julian
    Horch, Clemens
    Diepold, Klaus
    [J]. 2012 PICTURE CODING SYMPOSIUM (PCS), 2012, : 245 - 248
  • [23] Group-based social diffusion in recommendation
    Chen, Xumin
    Xie, Ruobing
    Qiu, Zhijie
    Cui, Peng
    Zhang, Ziwei
    Liu, Shukai
    Yang, Shiqiang
    Zhang, Bo
    Lin, Leyu
    [J]. WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 2023, 26 (04): : 1775 - 1792
  • [24] GRS: A Group-Based Recruitment System for Mobile Crowd Sensing
    Azzam, Rana
    Mizouni, Rabeb
    Otrok, Hadi
    Ouali, Anis
    Singh, Shakti
    [J]. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2016, 72 : 38 - 50
  • [25] Crowd-Based Observations of Riverine Macroplastic Pollution
    van Emmerik, Tim
    Seibert, Jan
    Strobl, Barbara
    Etter, Simon
    den Oudendammer, Tijmen
    Rutten, Martine
    Razak, Mohd Shahrizal bin Ab
    van Meerveld, Ilja
    [J]. FRONTIERS IN EARTH SCIENCE, 2020, 8
  • [26] Crowd-Based Assessment of Deformational Cranial Asymmetries
    Borchert, Kathrin
    Hirth, Matthias
    Stellzig-Eisenhauer, Angelika
    Kunz, Felix
    [J]. DIGITAL TRANSFORMATION FOR A SUSTAINABLE SOCIETY IN THE 21ST CENTURY, 2020, 573 : 145 - 157
  • [27] Crowd-based positioning of UAVs as Access Points
    Rautu, Dorin
    Dhaou, Riadh
    Chaput, Emmanuel
    [J]. 2018 15TH IEEE ANNUAL CONSUMER COMMUNICATIONS & NETWORKING CONFERENCE (CCNC), 2018,
  • [28] CrowdPlanner: A Crowd-Based Route Recommendation System
    Su, Han
    Zheng, Kai
    Huang, Jiamin
    Jeung, Hoyoung
    Chen, Lei
    Zhou, Xiaofang
    [J]. 2014 IEEE 30TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 2014, : 1144 - 1155
  • [29] Crowd-based Detection of Routing Anomalies on the Internet
    Hiran, Rahul
    Carlsson, Niklas
    Shahmehri, Nahid
    [J]. 2015 IEEE CONFERENCE ON COMMUNICATIONS AND NETWORK SECURITY (CNS), 2015, : 388 - 396
  • [30] Crowd-Based Recognition of Web Interaction Patterns
    Lasecki, Walter S.
    He, Grant
    Bigham, Jeffrey P.
    Lau, Tessa
    [J]. ADJUNCT PROCEEDINGS OF THE 25TH ANNUAL ACM SYMPOSIUM ON USER INTERFACE SOFTWARE AND TECHNOLOGY, 2012, : 99 - 100