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2023
Journal article
Open Access
Social search: retrieving information in online social platforms - a survey
Amendola M., Passarella A., Perego R.
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.Source: Online social networks and media 36 (2023). doi:10.1016/j.osnem.2023.100254
DOI: 10.1016/j.osnem.2023.100254
DOI: 10.48550/arxiv.2209.14369
Project(s): SoBigData-PlusPlus
Metrics:
Amendola M., Passarella A., Perego R.
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.Source: Online social networks and media 36 (2023). doi:10.1016/j.osnem.2023.100254
DOI: 10.1016/j.osnem.2023.100254
DOI: 10.48550/arxiv.2209.14369
Project(s): SoBigData-PlusPlus
Metrics:
See at:
arXiv.org e-Print Archive 
| Online Social Networks and Media | ISTI Repository | ISTI Repository | www.sciencedirect.com | doi.org 
| CNR ExploRA
2023
Journal article
Open Access
Social search: Retrieving information in Online Social platforms - A suvey
Amendola M., Passarella A., Perego R.
Social Search research studies methodologies exploiting social information tobetter satisfy user information needs in Online Social Media while simplifyingthe search effort and consequently reducing the time spent and the computationalresources utilized. Starting from previous studies, in this work, weanalyze the current state of the art of the Social Search area, proposing a newtaxonomy and highlighting current limitations and open research directions.We divide the Social Search area into three subcategories, where the social aspectplays a pivotal role: Social Question&Answering, Social Content Search,and Social Collaborative Search. For each subcategory, we present the keyconcepts and selected representative approaches in the literature in greaterdetail. We found that, up to now, a large body of studies model users' preferencesand their relations by simply combining social features made availableby social platforms. It paves the way for significant research to exploit morestructured information about users' social profiles and behaviours (as theycan be inferred from data available on social platforms) to optimize theirinformation needs further.Source: Online social networks and media 36 (2023). doi:10.1016/j.osnem.2023.100254
DOI: 10.1016/j.osnem.2023.100254
DOI: 10.48550/arxiv.2209.14369
Metrics:
Amendola M., Passarella A., Perego R.
Social Search research studies methodologies exploiting social information tobetter satisfy user information needs in Online Social Media while simplifyingthe search effort and consequently reducing the time spent and the computationalresources utilized. Starting from previous studies, in this work, weanalyze the current state of the art of the Social Search area, proposing a newtaxonomy and highlighting current limitations and open research directions.We divide the Social Search area into three subcategories, where the social aspectplays a pivotal role: Social Question&Answering, Social Content Search,and Social Collaborative Search. For each subcategory, we present the keyconcepts and selected representative approaches in the literature in greaterdetail. We found that, up to now, a large body of studies model users' preferencesand their relations by simply combining social features made availableby social platforms. It paves the way for significant research to exploit morestructured information about users' social profiles and behaviours (as theycan be inferred from data available on social platforms) to optimize theirinformation needs further.Source: Online social networks and media 36 (2023). doi:10.1016/j.osnem.2023.100254
DOI: 10.1016/j.osnem.2023.100254
DOI: 10.48550/arxiv.2209.14369
Metrics:
See at:
arXiv.org e-Print Archive | Online Social Networks and Media | ISTI Repository | www.sciencedirect.com | doi.org | CNR ExploRA