Human Information Interaction

Background and Aim. The promising outlook of easy communication incurring minimum cost has caused social networks to face increasing number of active members each day. These members develop and expand international communication through information sharing including personal information. Thus, big data analysis of social networks provides companies, organizations and governments with ample and unique opportunities to reach their strategic goals and various methods have been proposed in order to accomplish this objective. Each method has its own advantages, disadvantages and application area which would require deep study and assessment to understand. Therefore, the aim of this study is to investigate the approaches and methods of data analysis in social networks and study the advantages, disadvantages and application area of each method.

Method. This research is an applied research with qualitative approach and it was conducted using thematic analysis method and the study population include 35related conference papers, journal articles and reports published during 2010-2017.

Results. Various methods are used for the analysis of social networks and these methods are classified into three categories: quantitative, qualitative and mixed methods.

Conclusion. Due to the complex and multidimensional nature of social networks, the best approach is a mixed approach. This means combination of qualitative and quantitative methods and exploring various aspects of networks.