Reliable Online Social Network Data Collection

Abstract

Large quantities of information are shared through online social networks, making them attractive sources of data for social network research. When studying the usage of online social networks, these data may not describe properly users' behaviours. For instance, the data collected often include content shared by the users only, or content accessible to the researchers, hence obfuscating a large amount of data that would help understanding users' behaviours and privacy concerns. Moreover, the data collection methods employed in experiments may also have an effect on data reliability when participants self-report inacurrate information or are observed while using a simulated application. Understanding the effects of these collection methods on data reliability is paramount for the study of social networks; for understanding user behaviour; for designing socially-aware applications and services; and for mining data collected from such social networks and applications. This chapter reviews previous research which has looked at social network data collection and user behaviour in these networks. We highlight shortcomings in the methods used in these studies, and introduce our own methodology and user study based on the Experience Sampling Method; we claim our methodology leads to the collection of more reliable data by capturing both those data which are shared and not shared. We conclude with suggestions for collecting and mining data from online social networks.

Analysis of Questionnaires on User Behavior for Assessing Symptoms of Excessive SNS Usage

“…Researchers have studied it by collecting the data of SNS usage behaviors as a first step [9,[14][15][16][17][18]. Many types of data and collection methods exist.…”

“…Many types of data and collection methods exist. Abdesslem et al [16] summarized the existing data collection methods as follows: 1) Self-reported data:…”

“…Some studies employ automated script that automatically scans and crawls content from websites using HTTP requests/responses [14]. Other researchers collect data through a social network aggregator [14,18] or by tracing network traffic from Internet service providers (ISPs) [16]. However, some of the data available on SNSs cannot be collected with this approach.…”

“…This application monitors records and logs the operations and activities of users while they are using computers or smartphones and provides flexibility and privacy for data access [16]. Unfortunately, researchers need to install applications on user devices and manually get the data.…”

“…Abdesslem et al [16] believe that "more reliable data can be obtained by using a new methodology based on the combinations of existing methods: this way, the data collected come from different sources and describe better users' behaviors." Therefore, we employed self-reported and SNS measurement approaches and designed and developed a web-based application as a tool for aggregating data from questionnaires and SNSs by APIs [2,3].…”