Measuring interactivity and geographical closeness of Online Social Network users to support social recommendation systems

Several applications (e.g., Instagram, PiCsMu) integrate existing Online Social Networks (OSN) into the core of their solutions to explore social information. Although this integration enables more accurate social recommendation systems, the collection and monitoring of relevant OSN data by third-pa...

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Bibliographic Details
Main Authors: Machado, Guilherme Sperb, Bocek, Thomas, Filitz, Alexander, Stiller, Burkhard
Format: Conference Proceeding
Language:English
Subjects:
Authentication
Authorization
Calibration
Facebook
Filtering
Monitoring
Online Social Model
Online Social Networks
Recommendation System
Social Data
Twitter
Online Access:Request full text
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Summary:Several applications (e.g., Instagram, PiCsMu) integrate existing Online Social Networks (OSN) into the core of their solutions to explore social information. Although this integration enables more accurate social recommendation systems, the collection and monitoring of relevant OSN data by third-party applications is a challenging management task, since OSNs (a) impose rate restrictions to their Application Programming Interface (API) calls, (b) do not provide detailed information about specific OSN features, and (c) may provide incomplete or not up-to-date OSN data. Therefore, this paper covers the design, prototyping, and evaluation of JSocialLib, a new meta-API library for collecting OSN data from existing OSNs. It provides (1) an interaction- and (2) a location-based method in support of social recommendations systems.
ISSN:2165-9605
DOI:10.1109/CNSM.2014.7014157