AI Summary & Key Takeaways
AI InsightTo the best of our knowledge, ours is the most comprehensive OSN data collection effort and also the first study focused on the behavior of OSN users in Turkey.
📌 3 Key Takeaways
Abstract
Online Social Networks OSNs are extremely popular services that allow users to interact with each other and share content. Due to the large amounts of data shared by users, OSNs are also rich data sources for research in social network analysis. Studying the usage of OSNs helps to understand users' content-sharing behavior and privacy concerns. In order to do so, collecting data is a necessary first step. However, Application Programming Interfaces APIs provided by OSN providers have several limitations which make it difficult to access secured information. In this paper, we present the design and implementation of an OSN crawler, discuss the challenges of this task and our workarounds towards accessing public OSN data. Moreover, we perform analyses of the collected data to indicate users' sharing behavior and give a detailed discussion of these analyses from the perspective of individual privacy protection over OSNs. Our crawler overcomes most of the restrictions of OSN APIs and collects all forms of OSN user interactions as well as every bit of public data posted on an OSN. Most of the existing studies collect OSN data using focused crawlers and therefore are capable of collecting only the desired type of data. Our crawler, on the other hand, provides a holistic view. On the popular Facebook OSN, our crawler captures user relationships like kinship, friendship and attributes like profile items, events, posts, comments, replies, meta-data of activities i.e., posting time, location, tagged users etc. . To the best of our knowledge, ours is the most comprehensive OSN data collection effort and also the first study focused on the behavior of OSN users in Turkey.