Identification of User Patterns in Social Networks by Data Mining Techniques: Facebook Case
نویسندگان
چکیده
Currently, social networks such as Facebook or Twitter are getting more and more popular due to the opportunities they offer. As of November 2009, Facebook was the most popular and well known social network throughout the world with over 316 million users. Among the countries, Turkey is in third place in terms of Facebook users and half of them are younger than 25 years old (students). Turkey has 14 million Facebook members. The success of Facebook and the rich opportunities offered by social media sites lead to the creation of new web based applications for social networks and open up new frontiers. Thus, discovering the usage patterns of social media sites might be useful in taking decisions about the design and implementation of those applications as well as educational tools. Therefore, in this study, the factors affecting “Facebook usage time” and ”Facebook access frequency” are revealed via various predictive data mining techniques, based on a questionnaire applied on 570 Facebook users. At the same time, the associations of the students’ opinions on the contribution of Facebook in an educational aspect are investigated by employing the association rules method.
منابع مشابه
Opinion Mining, Social Networks, Higher Education
Background and Aim: With the advent of technology and the use of social networks such as Instagram, Facebook, blogs, forums, and many other platforms, interactions of learners with one another and their lecturers have become progressively relaxed. This has led to the accumulation of large quantities of data and information about studentschr('39') attitudes, learning experiences, opinions, and f...
متن کاملMining Facebook Data for Predictive Personality Modeling
Beyond being facilitators of human interactions, social networks have become an interesting target of research, providing rich information for studying and modeling user’s behavior. Identification of personality-related indicators encrypted in Facebook profiles and activities are of special concern in our current research efforts. This paper explores the feasibility of modeling user personality...
متن کاملPrediction of user's trustworthiness in web-based social networks via text mining
In Social networks, users need a proper estimation of trust in others to be able to initialize reliable relationships. Some trust evaluation mechanisms have been offered, which use direct ratings to calculate or propagate trust values. However, in some web-based social networks where users only have binary relationships, there is no direct rating available. Therefore, a new method is required t...
متن کاملAnalysis of Users’ Opinions about Reasons for Divorce
One of the most important issues related to knowledge discovery is the field of comment mining. Opinion mining is a tool through which the opinions of people who comment about a specific issue can be evaluated in order to achieve some interesting results. This is a subset of data mining. Opinion mining can be improved using the data mining algorithms. One of the important parts of opinion minin...
متن کاملIdentification of Fraud in Banking Data and Financial Institutions Using Classification Algorithms
In recent years, due to the expansion of financial institutions,as well as the popularity of the World Wide Weband e-commerce, a significant increase in the volume offinancial transactions observed. In addition to the increasein turnover, a huge increase in the number of fraud by user’sabnormality is resulting in billions of dollars in lossesover the world. T...
متن کامل