An Introduction To Social Web Mining And Big Data?

Open source intelligence based on social media in the 21st century is a vital component of the intelligence collection process. As people around the world use social media more it will become integral to the intelligence collection process. The advent of social media is significant to Military Intelligence because it provides access to literally billions of people providing information on events, people, and locations in real time at a low cost.

Social media being an ever growing industry, companies have incorporated their marketing and strategies to better their businesses. We explore that the reasons for the importance of incorporating this is: The daily use of handheld devices to access social media on a daily basis amongst computer use, Big data: online tracking produces oceans of data, challenging business analytics programs, Twitter, Facebook, and Pinterest

Abstract- Big data is a hot research topic in today’s world. Data has become an indispensable part of every economy, industry, organization, business function and individual. With the fast growth now-a-days organizations has filled with the collection of millions of data with large number of combinations. This big data challenges over business problems. Big Data is a new term used to identify the datasets that due to their large size and complexity. Big Data mining is the capability of extracting useful information from these large datasets or streams of data, that due to its volume, variability, and velocity. We address broad issues related to big data and/or big data mining, and point out opportunities which help to reshape the subject area of today’s data mining technology toward solving tomorrow’s bigger challenges emerging in accordance with big data.

The emergence of social web has changed the World Wide Web. This new concept was introduced in 1996 by Rheingold. In addition of the principle aim of the web that consists of an open access to information, the second generation of Web applications, Web 2.0 applications, has allowed for users to communicate effectively with each other. Hence, the web transformed from a web where most users were consumers passively viewing website (i.e. information) to a more active and participatory actors. Users are now consumers and contributors of information, so, the web has been transformed from a hypertext environment to a “web of people” environment that connects family, friends and colleagues enabling them to share different type of information. This paradigm has resulted to a new medium of communication known as User Generated Content (UGC) where users made together a substantial effort to publish and produce their own content in different ways and with various formats to enrich the web experience. This content can be produced with various formats that depends on the social media stream used, it cover (i) materials that users make available through blog, wiki and social media sharing services (e.g. YouTube , Instagram , etc); (ii) feedback such as comments, review, rates; (iii) and social network data including public profiles, social network structure and user interactions. Given the amount of information produced in social media platforms, new challenges were raised, which are

Big Data is an expansive phrase for data sets so called big, large or complex that they are very difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. In common usage, the term big data has largely come to refer simply to the use of predictive analytics. Big data is a set of techniques and technologies that need or require new forms of integration to expose large invisible values from large datasets that are diverse, complex, and of a massive scale. When big data is effectively and efficiently captured, processed, and analyzed, companies

The author points out that although there are existing algorithms and tools available to handle Big Data, they are not sufficient as the volume of data is exponentially increasing every day. To show the usefulness of Big Data mining, the author highlighted the work done by United Nations. In order to further enhance the reader’s perspective, the author provided research work of various professionals to educate its readers about the most recent updates in Big Data mining field. The author further describes the controversies surrounding Big Data. The author has first provided the context and exigence by elaborating on why we need new algorithm and tools to explore the Big Data. The author used the strategy of highlighting the logos by mentioning the research work of different industry professionals, workshops conducted on Big Data and was able to appeal to connect to the reader’s ethos. The author also used pathos by urging the budding Big Data researchers to further dig deep into the topic and explore this area

Social media has emerged as the most powerful form of communication these days. The ability to voice an opinion from anywhere over anything has coined and popularized the term ‘Global Citizen. Many social platforms available these days provide the avenues for the companies and organization to make a brand for themselves by directly engaging with their customers. If you don’t like some brand you bought or a movie you just watched, login on Twitter or Facebook and tell the world. These platforms provide an access into what is currently trending or making the stir at the moment. Thus, there is a huge repository of opinionated data that if harnessed strategically can help to solve problems ranging from what product to invest into complex business

The emergence of big data has provided different avenues for organizations to use data to improve different aspects of their respective operations. Be it customer service, research and development, or market position, Big Data has the potential to be a significant driving force in all these areas. However, there’s still a significant gap between the ability of Big Data to produce insightful analytical information based on real-time data and the ability of organizations to capture and utilize this readily available tool. This is, in part, due to the fact that the systems and processes necessary to fully maximize the usefulness of Big Data is currently lacking in most organizations. This lack of a conducive habitat for Big Data is further magnified in new organizations without any knowledge of Big Data. For organizations that have that have little to no knowledge of Big Data, there must be a thorough assessment of the benefits of big data and how they could improve the organizations overall place in the market. There also needs to be steps taken towards the design of frameworks that will enable the organization to better capture and utilize Big Data.

Understanding and utilizing big data, such as the kind gathered en masse from social media and internet browsing searches can be a useful tool to combat terrorism domestically and abroad. It allows for connecting the dots of an individual’s online footprint to potentially identify terrorists before they strike.

The purpose of big data in the building of future cities is to make them smarter and more sustainable (Build the cities). The idea of a city being smart sounds crazy, but with all the technology people have on hand at all times allows this to be possible. Again, a large part of the data comes from social media, and the interactions between individuals. Researchers are now trying to use social media in a new way, to get the world out about social issues, environmental issues, etc. to see how people react and if they react. For example, researchers are using social media to create climate awareness, by asking to reduce carbon dioxide emissions and energy waste in urban area (Marr, 2015). In the analysis of their reactions, researchers will be able to provide useful information on how to best shape the future of cities (Heppenstall & Malleson, 2015).

Each research should have a basis on how the process is performed to ensure that the conclusion and information learned is accurate and appropriate.

Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.

Twitter added $47.5 million were to its coffers in 2013. This was not advertising revenue, but income generated by selling user data to businesses hungry to find new consumers. By researching target consumer buying habits, businesses can find more consumers and invariably increase profits. Because of this, big data is a highly sought after business asset; however, mining that data is a complex task.

The term “Big Data” has been around for quite some time and has been catching everyone’s attention with remarkable speed. A plethora of questions do pop up in our mind sometimes. What is big data, is this something absolutely new, how can it be leveraged to create value for an organization and so on. For many years, companies have used various transactional records stored in relational databases to make competitive business decisions. But how long can we sustain or depend on these traditional methods of doing analysis and coming to a conclusion. There is an ocean of non-traditional, less structured data such as weblogs, social media, email, sensors, and photographs that can be mined not only for useful information but also to make strategic decisions.

Market research strategies have completely been redefined as a result of the array of information available due to social media and social networks. Organizations now face data overload, and are looking to increase both data breadth and data thickness. The most efficient and successful organizations are able to recognize this and adapt their strategy in order to incorporate social media and social data into its current market research techniques. There are six major benefits of using social data for marketing research; these include tracking trends for real time insights, learning the language of your audience, using real time aspects for quick research, broadening the scope of market research, discovering unnoticed trends, and harnessing