Social Media Data Mining Techniques: A Survey

Author(s):  
Dimple Tiwari ◽  
Manoj Kumar
2019 ◽  
Vol 8 (4) ◽  
pp. 8574-8577

The unavoidable utilization of online networking like Facebook is giving exceptional measures of social information. Information mining methods have been broadly used to separate learning from such information. The character of the person is predicted whether he is good or not by using data mining techniques from user self-made data. Mining methods are being broadly using to separate learning from such information, main examples for them are network discovery and slant investigation. Notwithstanding, there is still a lot of room to investigate as far as the occasion information (i.e., occasions with timestamps, for example, posting an inquiry, altering an article in Wikipedia, and remarking on a tweet. These occasions react users' personal conduct standards and working forms in the social media websites.


2017 ◽  
Vol 10 (3) ◽  
pp. 644-652
Author(s):  
Asha Asha ◽  
Dr. Balkishan

Escalating crimes on digital facet alarms the law enforcement bodies to keep a gaze on online activities which involve massive amount of data. This will raise a need to detect suspicious activities on online available social media data by optimizing investigations using data mining tools. This paper intends to throw some light on the data mining techniques which are designed and developed for closely examining social media data for suspicious activities and profiles in different domains. Additionally, this study will categorize the techniques under various groups highlighting their important features, challenges and application realm.


In the world of digitalization the data play a key role. The data may be in structured or unstructured. The structured data uses data mining techniques to find the unknown pattern from the known data. But, the social media has huge data due to its rapid growth, the data were dynamic and unstructured. Due to this traditional data mining techniques will not be appropriate. The combinational approach of data mining and social media will provide the user to gain an insight and prominent idea how can be mined. Social media provides each individual to connect with the others depending on their interest. Every individual are accessing Face book, Twitter, LinkedIn, cademicia.edu, Google+ for sharing their views and thoughts, day-to-day happenings with any one or more of the above sites. This paper give an idea of the how those sites are classified based on their size, data, research focus, design issues and the types of the sites, types of users and the common approaches on social networks which will help the researchers how the social media, social networking websites structurally classified, studies the existing data mining techniques along with the performance metrics used in past researches and tools for retrieving social media data.


2018 ◽  
Vol 03 (03) ◽  
pp. 1850003 ◽  
Author(s):  
Jared Oliverio

Big Data is a very popular term today. Everywhere you turn companies and organizations are talking about their Big Data solutions and Analytic applications. The source of the data used in these applications varies. However, one type of data is of great interest to most organizations, Social Media Data. Social Media applications are used by a large percentage of the world’s population. The ability to instantly connect and reach other people and companies over distributed distances is an important part of today’s society. Social Media applications allow users to share comments, opinions, ideas, and media with friends, family, businesses, and organizations. The data contained in these comments, ideas, and media are valuable to many types of organizations. Through Data Mining and Analysis, it is possible to predict specific behavior in users of the applications. Currently, several technologies aid in collecting, analyzing, and displaying this data. These technologies allow users to apply this data to solve different problems, in different organizations, including the finance, medicine, environmental, education, and advertising industries. This paper aims to highlight the current technologies used in Data Mining and Analyzing Social Media data, the industries using this data, as well as the future of this field.


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