Modern era social networking has been revolutionised with the advent of Web-based social networking systems. This kind of communication platform is technically termed as a social networking site (SNS). The social networking sites have collectively given rise to social media networks that facilitate real-time communication and information sharing across the globe. Major social networking websites in the world such as Facebook, Twitter, Google Pulse, etc. generate lots of time critical dynamic data. The Pew Research Center (2014, p. 1) has described social media in the following words:
“Social media include all the ways people connect to people through computation. Mobile devices, social networks, email, texting, micro-blogging and location
These network structures can be visualised, analysed, and processed to generate network insights. The network insights are used to obtain valuable information on different aspects of social media functions, structures, variations, and behaviours.
Data mining can help in manipulating social media data more effectively. According to Gundecha and Liu (2012, section 1.1), data mining can be defined as “a process of discovering useful or actionable knowledge in large-scale data.” Given the diversified nature and hugeness of social media data, implementation of data mining techniques has emerged as a coveted alternative to conventional social network analysis (SNA) methods. In this paper, the main focus area is the field of data mining with reference to social media analysis and research.
2. Literature
Instead, social media data and its features must be understood on the basis of data sources and network models related with them (Zafarani, Abbasi, and Liu 2014).
2.2 Application of data mining The state of the art of modern data mining technologies is highly complex, rich, and purposive. According to Han, Kamber, and Pei (2011), basic essentials of data mining include pre-processing, supervised and unsupervised learning, algorithmic manipulation, and effective organisation. Furthermore, clear understanding of graph essentials, network measures, and network models (see Figure – 2) is extremely necessary for implementing a “social media mining” (Zafarani, Abbasi, and Liu 2014, p. 1) framework
According to Gundecha and Liu (2012), the major aims of a data mining process include manipulating large-scale data and deciphering actionable patterns in them.
“Because social media is widely used for various purposes, vast amounts of user-generated data exist and can be made available for data mining.” (Gundecha and Liu 2012, section
Abstract:- This paper presents a brief idea about data mining, data mining technology, and big data. The applications regarding data mining will also be discussed briefly. The main cause of data mining is to get different ideas, how to access big data by different tools.
Social media is the fruit of the current Web 2.0 technology. It is a series of organized applications which need to have internet connection to realize their functions of producing and interchanging of the contents generated by users (Kaplan & Haenlein, 2010). To be clearer, the social media is what we use to exchange information in daily life through internet. The implementation of social media can be found all around us, especially with the development of portable devices, and easier internet access. With constant upgrading on mobile platform, and the efforts of internet suppliers, more and more people can now enjoy the social media applications and media web sites with a relatively lower constraint by time and space. Through using social media tools, people can receive or deliver information quicker and more effectively. The implementation of social media has made the earth smaller. Thus, it may bring about many impacts which may significantly change people’s lives.
Data mining is a combination of database and artificial intelligence technologies. Although the AI field has taken a major dive in the last decade; this new emerging field has shown that AI can add major contributions to existing fields in computer science. In fact, many experts believe that data mining is the third hottest field in the industry behind the Internet, and data warehousing.
Data mining is a field that is a combination of numerous other fields such as the database research, artificial intelligence and statistics. Data mining involves looking for patterns in vast amounts of data as a part of knowledge discovery process. (Huang, Joshua Zhexue, Cao, Longbing, Srivastava, Jaideep, 2011) contains numerous papers that are solely dedicated to discussing the advancements that have been made in the field of data mining and knowledge discovery. A lot of people have performed a thorough research on all that has been done in data mining and the future possibilities that are soon to be implemented practically. The research not only covers the history and the reasons that led to various advancements being made but they also cover the detail models of the proposed solutions to deficiencies in existing systems.
The key objective in any data mining activity is to find as many unsuspected relationships between obtained data sets as possible to be able to achieve a better understanding on how the data and its relationships are useful to the data owner. The potential of knowledge discovery using data mining is huge and data mining has been applied in many different knowledge areas such as in large corporations to optimize their marketing strategies or even to smaller scale in medicinal research where data mining is used to find the relationship patient’s data with the corresponding medicinal prescription and symptoms.
The Culture of Connectivity (Dijck, 2013) explored the changing face of social media as it evolved with the advent of Web 2.0. We now have large corporations accomplishing more than just facilitating connection, they have created global information and data mining companies that extract and exploit user connectivity. The development of this connectivity by preeminent social media platforms such as Facebook and Twitter has influenced, transformed and constrained the potential for connection via social media. There have been fundamental changes in social media and this connectivity is not without controversy.
The Internet users might have a profile (sex, age, education level, etc) to receive the most appropriate information according to their needs. The contemporary benefit of technology innovation is that automatically the “sender” has the chance to deliver the more appropriate message according to the needs of the user (Burns. 2016). Social media (Facebook, Instagram, Twitter, Linkedin, etc.) gain ground on a daily basis, and stakeholders have particular benefits by using them (Internetlivestats.com, 2017). To interpret the definition of social media, it is mandatory to understand the structure of the Social media. As (Kay peters 2013)
Today, the topic of data mining has much interest in government, business, and research circles. With the growth of computer use within these areas has also come a greater desire to let the computers do the work that used to be done by humans. The problem, nowadays, is that the data that needs to be analyzed has become too large and cumbersome for one person or even teams of people to envision tackling without help from computers. These computers are no longer mere crunchers of numbers but now they find the patterns that the humans used to find. From this growth has arisen a vast body of knowledge concerned with this process of data analysis. As with much other information, the Internet is employed to make available the ever-growing body of information on this topic. Many general sources of information [a,b,c] are now online. These are updated and expanded upon almost a constant basis. The use of the Internet to disseminate and collect information is itself a consideration in this field. The amount of information is expanding at such a rate that old methods of information disposal, such as paper journals and b...
In 2001, the MIT Technology Review listed data mining as one of the top 10 technologies that will change the world.[i] So, what is data mining? For many people, the simple answer is that data mining is the collecting of people’s information when logged onto the Internet. But Webopedia emphasizes that data mining is not the collection of data itself, but the statistical interpretation of it – allowing people to obtain new information or find hidden patterns within that collected data.[ii] It is the combination of these, collection and analysis, which are cause for concern. People want to know: What information is being collected about me? Who has access to that information? What decisions are people making about me based upon that information?
It is completely essential to discover more about discovering Big Data with social media analytics.
This world as we know is heading towards a more virtual era, where everything we need to know is under the palm of our hands. We have many devices such as smart phones, tablets, computers, which gives us access to an infinite amount of information. This virtual life style we are becoming accustomed to introduced us to social media. An increase amount of interaction is being built between known and unknown users from all around the world. Social networks such as Facebook, MySpace, twitter, and even tumbler have become an everyday routine of our daily lives. In this modern society, all these social media websites have brought about a significant amount of impact in many of us. It has really influenced its users on how to conduct their lives.
Social media is very effective in facilitating knowledge sharing and brings about good opportunities for organizations. Not only does Social Media enhance people-to-people connections, it also simplifies the processes of people-to-data access (Hansen et al., 1999). Personalization-based technologies, coupled with codification-based technologies connect knowledge owners and knowledge seekers, expediting the exchange of tacit knowledge. Social media technologies encourage easy access to knowledge residing in experts’ minds through bridging the temporal and spatial gaps between knowledge seekers and knowledge owners. Moreover, social media allow people to maintain vast interpersonal connections which can be strong enough to foster trust, common value, and deep understanding, thus catalyzing even more forms of knowledge-sharing between users (Baehr and Alex-Brown, 2010). Concurrently, the diversified connections enable even more elaborated communication, collaboration and thus innovation, spurring on new knowledge and perspectives (Gray et al.,
Social media has become a major epidemic in today’s society. According to millions of people have signed up on social media websites, allowing their basic information to be shared with the world wide web. Two of the biggest social media websites today are Facebook and Twitter. The new generation tends to use Twitter over Facebook, the older generation prefer Facebook over Twitter. Though Facebook and Twitter serve the same purpose and have many similarities, they both differ in many ways.
Nowadays, social media is growing very rapidly throughout the whole world. Social media has changed the way that we communicate with others through using these common social networking sites like Face book, Twitter, and Instagram…For that, social media has positively and negatively impacted our life.
The growth of social networking is one of the fastest growing digital trends to exist. Many social networking sites boast with millions if not billions of members. Prominent examples of these social sites are Facebook, Twitter, and LinkedIn. Members of these networks use them daily to communicate, share various types of information or to collaborate with other members.