Social search: Retrieving information in Online Social platforms - A survey

被引:2
|
作者
Amendola, Maddalena [1 ,2 ]
Passarella, Andrea [2 ]
Perego, Raffaele [3 ]
机构
[1] Univ Pisa, Dept Comp Sci, I-56127 Pisa, Italy
[2] Natl Res Council CNR, Inst Informat & Telematics IIT, I-56124 Pisa, Italy
[3] Natl Res Council CNR, Inst Informat Sci & Technol ISTI, I-56124 Pisa, Italy
来源
ONLINE SOCIAL NETWORKS AND MEDIA | 2023年 / 36卷
关键词
Social search; Search in online social networks; Social information retrieval; Community Question Answering; QUESTION RETRIEVAL; COMMUNITY; RECOMMENDATION;
D O I
10.1016/j.osnem.2023.100254
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Social Search research studies methodologies exploiting social information to better satisfy user information needs in Online Social Media while simplifying the search effort and consequently reducing the time spent and the computational resources utilized. Starting from previous studies, in this work, we analyze the current state of the art of the Social Search area, proposing a new taxonomy and highlighting current limitations and open research directions. We divide the Social Search area into three subcategories, where the social aspect plays a pivotal role: Social Question&Answering, , Social Content Search, , and Social Collaborative Search. . For each subcategory, we present the key concepts and selected representative approaches in the literature in greater detail. We found that, up to now, a large body of studies model users' preferences and their relations by simply combining social features made available by social platforms. It paves the way for significant research to exploit more structured information about users' social profiles and behaviours (as they can be inferred from data available on social platforms) to optimize their information needs further.
引用
收藏
页数:15
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