مقاله انگلیسی رایگان در مورد یک رویکرد برای تشخیص تنظیمات کاربر بر اساس تجزیه و تحلیل شبکه های اجتماعی – الزویر 2019

1- Introduction

2- Theoretical background

3- Identifying user preferences using SNA

4- Results

5- Discussion and conclusion

References

Abstract

This paper introduces an approach for identifying user preferences using social network analysis (SNA). Main idea was to reduce complexity and enable effective and affordable social network analysis harnessing particular tools and techniques. As a proof of concept, we performed the research that included two sources: (1) the control data source — analytical data collected from mobile application FilterApp for cultural events and (2) the experimental data source — data based on survey for users of the mobile application. The results revealed three clusters of cultural events based on user preferences towards certain types of cultural events, the frequency of visits to cultural events and the size of groups when visiting these events. The obtained conclusions were used to develop system of recommendations and for customization of offer and marketing strategies according to the identified users’ preferences. The main value of this paper is reflected in the clearly defined research process with all the phases from data collection to validation of results.

Introduction

Social network services include a plethora of personal, business and educational interactions among users. Data generated within social networks represents an input for social computing. The term social computing refers to an emerging concept that enables analysis of users’ profiles, as well as their interactions and behaviors [1]. Discovered information could be used in various contexts. For example, results of social computing research can lead to new targets and facilitate the process of introducing new products or services [2]. By introducing social computing online services, sharing of knowledge, experience, equipment, and resources can be increased among individuals, companies and research groups [3]. Social computing facilitates collective actions and social interactions by using various applications and services for multimedia content exchange and knowledge aggregation [4–6]. Social networks are the most explored part of social computing. Social Network Analysis (hereinafter: SNA) is the result of harnessing social computing in the analysis of social networks. SNA represents an interdisciplinary methodology for mapping and measuring of relationships and flows between people, groups, organizations, computers, URLs, and other connected information entities [7]. SNA collects the data important for market research, making business decisions, analysis of marketing activities, identification of influential users of social networks, determining the interconnection of users of a particular social network, etc. This paper shows an approach to identifying user preferences based on social network analysis. The main aim of the paper is to investigate possibilities of harnessing SNA for determining users’ preferences in the context of cultural events. The paper should contribute to the literature by introducing an approach that enables SNA that is not dependent only on data from well known social networks, i.e could be performed on data from domain specific social network.