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Über dieses Buch

This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on knowledge extraction, prediction, and decision-making in the context of individual, social, and national development. The content is divided into three main sections: the first of which discusses various approaches associated with Big Data Analytics, while the second addresses the security and privacy of big data in social media, and the last focuses on the literary text as the literary data in Big Data Analytics. Sharing valuable insights into the etiology behind human cognition and its reflection in social media and literary texts, the book benefits all those interested in analytics that can be applied to literature, history, philosophy, linguistics, literary theory, media & communication studies and computational/digital humanities.

Inhaltsverzeichnis

Frontmatter

Chapter 1. The Concept of Cognitive Social Media and Cognitive Literary Studies

Abstract
The chapter elucidates the basic concept of cognitive social media, features, and identical semiotics of cognitive social media. While exposition of cognitive social media and literary studies, the author lays emphasis on how both the streams of knowledge require Big Data Analytics. Based on the conceptual background, the author computationally studied Shahid’s and Faiz Ahmad Faiz’s Poetry, translation as a medium of reformation, translation as cultural human capital using Atlas.ti, the software. The chapter hence responds to the questions of how and why Big Data Analytics should be practiced in the domains of Humanities and Social Sciences. To justify Big Data Analytics as a cognitive social and humane technique, the author demonstrated the ways to challenge the factors of failure BDA devising W5 Formula in BDA, interpreting the meaning of BDA, the seminal factors of BDA criticism, and types of analysis.
Valiur Rahaman

Chapter 2. Big Data Analytics for Market Prediction via Consumer Insight

Abstract
Big Data is the soul of today’s market. The idea of scaling and enhancing any market to its greater potential without considering Big Data is hooey. A prodigious number of data is generating today. Around 1.7 mb of data by each person is being spawned per second today. This data helps to get a greater insight into some sort of pattern. Predictive analytics is performed on this prodigious history data. Predictive Analytics predict the future outcomes or events, previous or history data with the help of various techniques and models including Machine Learning Models, Forecasting Models, Statistical Modeling, Pattern Prediction, Visualization, etc. Big Data has embedded a gigantic potential concealed within it. The analytics of several hidden aspects of Big Data helps companies to predict all the dimensions of the market in the future. A gigantic number of data is spawned on social media. Billions of accounts are activated on these platforms, which results out in producing the flood of data. Predicting this Big Data has leveraged in several dimensions. The Big data can be utilized for predicting the future sales results, finding the potential customers, impact of advertisements or campaigns upon some strategy. With the help of big data, segmentation of non-resembling customers, targeting the most profitable group of customers and positioning of related advertisements, and campaigns to captivate that particular segment of customers can be performed. In marketing, the behavior being manifested by the individual customers at different time spans is predicted for listing out all the potential customers for the market. As the market depends upon the response of the customers and their satisfaction with the product, the surveys such as their satisfaction with the salesperson, satisfaction with the product, will they recommend the product to someone else are used as the data for finding the future possibility of the customer to come back. Similarly, activities of the users on the social media platforms help the marketers to know a lot about the likes, dislikes, and cognitive process of theirs, which ultimately helps them to segment the clients and target the important group of clients. In this chapter, we will elaborate the concept of Predictive Analytics, Market Prediction, Prediction of customer behavior using Big Data Analytics, Big Data Analytics for Cognitive science and social media, and the process of Big Data Analytics for market prediction.
Hemant Kumar Soni, Shivam Sharma

Chapter 3. Deconstructive Big Data Analytics: Literary Texts Analysis Through Atlas.ti Software

Abstract
The chapter delineates the conceptualization of deconstructive Big Data Analytics (DBDA) or studying semantic values of literary texts. In doing so, deconstruction is defined in terms of its developer Jacques Derrida’s philosophy of interpretation and its relationship with data analysis. Big Data is significantly a galaxy of networked data which requires its close reading to visualize its webbed constellations. Big Data Analysis demands the art of finding hidden meanings, disseminates each thread and fibers of data to let visualize the meanings and their contexts distinctively. When Big Data Analysis is used for experimental findings, being a bit different from what established findings are and that needs reverse study of data. The hypothesis of the chapter is that, deconstruction is used for bringing novelty and originality of results of each discovery, though it changes its nomenclatures in the existing world of knowledge. Relying on reviews of literature, researchers, and applications in social media, the authors explicate how deconstruction is practiced outside humanities and social sciences. In this context, application of deconstruction in science and technology would be studied focusing on how the application of deconstructive principles can benefit the knowledge of Big Data Analytics. Hence, the chapter would establish a novel theory of deconstructive big data analysis (DBDA), and feasible uses and functions of DBDA in the study of cognitive social media.
Valiur Rahaman, Aziz Haider

Chapter 4. Study of Big Data Analytics Tool: Apache Spark

Abstract
In this chapter, we remark on machine learning and Big Data with their sample applications, process, and commonly used machine learning techniques like classification and clustering. These techniques are used to explore, evaluate, and leverage data. Also, tools and techniques that can be used to develop machine learning schemes to learn from data (or, Big Data) will be discussed. In addition to this, the role of distributed computing platforms like Apache Spark in applying machine learning to Big Data will be presented in detail. Apache Spark is a general-purpose cluster computing framework which works on the principle of distributed processing. It is open-source software used for fast computing. On receiving data, it can immediately process it. Apache Spark deals with historical data using batch processing and real-time processing. Machine learning is a subfield of Artificial Intelligence. Its main focus is on learning models that can be learned by experience (which is data in the case of machines). For example, a machine learning model can learn to recognize an image of a Dog by being shown lots and lots of images of Dogs. In this chapter, we assume that a reader has a basic understanding of Machine Learning. Ongoing through this book chapter, readers will be able to:
i.
Machine learning with Big Data, characteristics, sources, and applications are discussed.
 
ii.
Understand the comparative working of Apache Spark.
 
iii.
Analyze the various types of problems to identify suitable techniques.
 
iv.
Develop models using open-source tools like Skill Network Lab and IBM cloud.
 
v.
Explore problems of Big Data using machine learning techniques with Apache Spark.
 
Gend Lal Prajapati, Rachana Raghuwanshi

Chapter 5. Contemporary Social Media and IoT-Based Pandemic Control: Exploring Possibilities of Big Data Analytics for Healthcare Governance

Abstract
The chapter explores transdisciplinary studies in IoT-based healthcare solutions, their representation through Social media big data. The current situation demands attention to develop socio-cyber spaces from where control and data related to trace, track, and control be possible. The current pandemic has been the subject matter of literary arts and social media. Whenever a lockdown situation happens in a country or the state closure is in an effective mode due to an epidemic or pandemic, the mass writing helps people to be aware of the real-time situation. Nowadays technology is added to this task of the mass writing and explores wisdom regarding the problems. Presently, as Coronavirus is spreading globally, we do not have a choice but to accept government policies to maintain social distancing to control the spread of this virus, but it is not easing for everyone to sit at home in isolation. During this pandemic across the world, social media is a resource for people to stay connected virtually, helps to engage and entertain people, and to spread positivity around. Social media has come to our rescue more than ever and helping us to cope with the quarantine. Applications like WhatsApp, Facebook, Twitter, LinkedIn keep everyone connected with his/her  family, friends, and colleagues who are quarantined during the period.  Hence the chapter reflects the aspect of cognitive function of Social media. From online meetings to sharing homemade recipes, to online classes and getting an update on COVID-19. Social media compensates  our boredom during this pandemic. The authors observed that the compensation caused a psychological displacement in people. For example, the doctors uses social media to educate people about COVID-19. The YouTube live streaming classes for better learning which enhances the growth of a kids, is another example. The user information collected on social media platforms allows marketers to have a better understanding of the customer behavior, target audience groups, and engagements. Based on these reviews, the chapter attempts to explore the immaculate use of IOT and Big Data Analytics for healthcare governance. 
Barkha Singh, Neha Firdaush Raun, Nagendra A. Sole

Chapter 6. Analyzing Women Health-Related Quality of Life Using Sentiment Analysis on Social Media

Abstract
Domestic Violence (DV) against women is now widely recognized as a severe and pervasive issue. Violence Against Women (VAW) is a big issue in terms of social care, well-being, personal health care but also a breach of human rights. Social media offer new ways of connecting, networking, and creating a community. The research considers on the consequences of violence against women on mental health. Psychological health statuses were measured based on the messages, which included the terms such as depression, suicidal thoughts, and satisfaction in life. The algorithm classifies the record distinct VAW trends and effects in mental health. The dataset is collected from Indian women blogs, corpus derived from Reddit and Twitter chats. The classification algorithms applied on the dataset are model for Logistic regression, Decision Tree model, Random Forest, and model for Deep learning. The statistical findings on datasets obtained a classification performance efficiency of up to 92%. The experimental findings with high classification accuracy provide an efficient method for understanding a major social issue against Women through social media.
U. K. Sridevi, S. Sophia

Chapter 7. Necessity of Big Data Analytics in Social Media for Questioning the Existence and Survival of Women and the Marginalized People

Abstract
Many factors have caused an absolute upheaval across the globe, the Pandemic is one of them. It has proved to be so intense and pervasive that the humanity is compelled to confine itself within its threshold and is struggling to find the means of survival with the outbreak of this Pandemic. India is not an exception to this impact. The question for existence and survival of women was often ignored in patriarch societies. Women is portrayed as a subordinate and dependent upon men, though she plays pivotal role to make homely lives stable under a roof. The chapter sets up an epistemic enquiry why women and the marginalized are crushed during social, political, and pandemic crisis in the course of the history of humanity; and how social media has heled challenging these dehumanizing issues. The authors conceptualize the cognitive factors of women’s suffering and the suffering of the marginalized during pandemic lockdown. Due to pandemic situation, lockdown or public curfew causes a family to come under a roof for many days. Both dependent and self-dependent women wait for means of earnings; daily wages suffer a lot due to the uncertain curfew. Do we have any dataset of women’s exploitations, domestic violence, and death ratio of the marginalized community during pandemic lockdown? Answering to this question, the chapter defines specific reasons for their unquestioned suffering with emphasis on exploring research in Big Data Analytics for coverage of DV cases, preventions, and controls so that policies can be developed in their favors esp. in pandemic days.
Valiur Rahaman, Supriya Agarwal

Chapter 8. Big Data Analytics and Cybersecurity: Emerging Trends

Abstract
At the current digital age, cybercrimes are increasing vastly. The strategies and tools preventing sophisticated cyberattacks and crimes cause organizations to stay intelligent with developing dangers. Big Data Analytics plays a crucial role when it comes to operational intelligence and security. This chapter aims to present a comprehensive cutting edge of Security Analytics, i.e., its trends, tools, technology, and description. Similarly, the work is engaged in three sorts: supervised, unsupervised, and hybrid approaches. The theoretical model developed in the chapter is based on the three types of machine learning, allowing the P.C. to learn and get to sample information without being customized to predict each conceivable circumstance. A structured work was applied to synthesize the theoretical model. A search of the existing literature is done on different websites, Scopus and Google Scholar, applying a mix of keywords such as Big Data Analytics, cybersecurity, and security analytics. This chapter will put forth the ideas and emerging strategies available to work with Big Data to lay out a future vision. Hence, it aims to persuade the imminent reader about emerging applications/trends of analytics as a cybersecurity solution later.
Sakshi Aggarwal, Stavros Sindakis

Chapter 9. Seizing the Networked Crime: Legal Framework for the Governance of Social Media Crimes in India

Abstract
Human beings are social animals. In 1943, renowned Psychologist Abraham Maslow, through his “A Theory of Human Motivation” emphasised on the importance of social affiliation, recognition, love, and belongingness in an individual’s life. With the advent of modern technologies like computers and smartphones and the social needs of human beings provided the thrust for the development of the virtual platforms for interactions and information, what we refer today as social media. Social media has become a mirror of society today. The debate on the impacts of social medial, both positive and negative, has conquered almost all spaces for deliberation and new avenues for discourse. The Internet Crime Report, 2019 suggested that India ranks third among the top 20 countries in the world with victims of cybercrime, including social media crimes. The objective of this paper is to throw light on the framework that takes hold of social media crimes in India. This a review paper that builds on the analysis of available literature to provide an understanding of the social media crimes and the formal constitutional provisions that safeguards the citizens from the networked crimes in India. The paper discusses the Information Technology Act, 2000, the draft Personal Data Protection Bill, 2019 and important sections of the Indian Penal Code to prevent the interest of users and crimes against them.
Urvashi Pareek, Nagendra Ambedkar Sole

Chapter 10. Toxic Masculinity and Inherent Misogyny on Social Media: Preventive Laws and Indian Judicial Approach

Abstract
Since last two decades the term masculinity has become a catchword all over the world. It may be seen with reference to social political, economic, and cultural as well. This has been expressed with reference to the manhood and gender equality most of the times. Inherent misogyny is an idea which defines social relationship of patriarchal society. Some of the prominent and progressive criminologists contradict the statement. Indeed, the term is coined with the social media as the platform has changed observing application and existence of virtual world. Deep rooted gender inequalities thinking has been shown on Social media platforms like Facebook, Whatsapp, and Instagram etc. Nowadays people have started using these platforms for destructive purposes. The example is “Bois locker room” a group created by some teenagers and later disclosed using nude pictures, offensive comments, sexual violence against women (Bose in BOIS locker room, Khan, Nakshab. BOIS locker room.). Author referred to the term toxic as bullying and sexual harassment that has reflected through different platform on social media. Indian judiciary during 1980s has given a judgment indicating the approach of gender equality and manhood (1997). Later on Indian legislature came with legislation and one of the major legislation which may be like a prevention, i.e., Information Technology Act, India (The Information Technology Act (2000). The Indian judiciary has proactively dealt with such emerging problems in the virtual world. In this chapter, authors try to analyze the developing approaches of toxic masculinity, inherent misogyny on social media and preventive laws and judicial approaches in India.
Ajay K. Barnwal, Anuja Mishra

Chapter 11. Quantifying Human Sentiments Using Qualitative Approach with Semantic-Sentiment Analysis

Abstract
Human sentiments’ quantification has evolved and gained imminence in the business as well as academics. Data analytics, as it has done for other domains, has also penetrated and given great tools for quantifying human sentiments and for the analysis of it, called text analytics. Increasingly, qualitative research techniques must be integrated with text analytics tools like the semantic analysis. This integration gives a more robust and pragmatic option to explore the overlooked variables that lie in the net of ceteris paribus. Systems are increasingly moving toward the simultaneous haptic exchange of semantic and sentiment analyses and quantification of sentiment and targeting. From a praxis point of view, knowledge and a practice system in a non-haptic management consulting context are presented here.
Joy Mukhopadhyay, Arka Ghosh

Chapter 12. Cognitive Transformation Through Social Media

Abstract
Social Media has a significant effect on both individuals and society. Here, firstly, the present condition of the social media is illustrated, with respect to the facts and statistics before deepening the aspects that are selected from the novel forms of interactions virtually. Specifically focusing on the recent findings in neuroscience research, there are some main questions that have to be answered: How do people deal with these latest types of technologies, and what are the likely consequences of our online behavior socially. A wide range of different interpretations exists in relation to the value of social media as a potent source of learning and communication. In the course of observing the different advantages and drawbacks, the highlight is on the situations for handling social media responsibly. This testing is done on two levels; Global and individual forms of information and the expression of opinions through social media and the impact of social media on real social systems. Further, social media affects the above two levels and this effect is integrated into a broader scenario. As quoted by Ruskin Bond while referring to the current social media structure and usage, “We live in a world where there are more writers than readers”. As a key result, we can conclude that there is an effect of social media on human thinking and as a result on peoples’ quality of life. Besides, emotions are key to communication and the benefits that are known generally may often pose a serious threat to the individuals and society on the whole and hence, there is a need for social media interactions that are sensible.
Nymphea Saraf Sandhu, Sanjiv Sharma

Chapter 13. Understanding Digital Diaspora as Cognitive Social Media: Necessity of Big Data Analytics for Peace and Harmony

Abstract
The chapter presents a review of research work in Diaspora and Digital Diaspora. In the chapter, Diaspora is defined as forced migration of the mass from their homeland to the other county and expatriate experiences. The hypothesis of the chapter is that diaspora experience is often traumatic, violent, and cognitively affected by an intense feeling of isolation of the individuals, and to avoid the bitter or inhuman consequences to human society, the sufferers have developed Web 2.0-based platforms called rostrum of digital diaspora where possibilities of expression provide a sense of belongingness to nostalgic and homeless immigrants. The chapter delineates how digital platforms work as social media to help cure the diaspora or expatriate trauma. Hence, to such platforms, the authors call Digital Diaspora as Cognitive Social Media (DDCSM). To explore the concept of digital diaspora, the chapter provides focuses on the basic concepts of diaspora, its singularity, the meaning of diaspora, and diaspora experiences based on the textual illustrations of global diaspora and expatriate literary writings, and how the big dataset of diaspora experiences available in cyberworld work effectively to bring peace and harmony in a global society. Hence, the chapter ends with implications and research questions of whether Big Data Analytics is required for mass-peace and harmony through its viable utilization, i.e., diaspora network analysis. The chapter illustrates the Big Data Analysis of Afghanistan Online and Somalinet which are two social media platforms that have the potential to change and upgrade the bent of minds of people.
Ajay Kumar Chaubey, Valiur Rahaman

Chapter 14. Data Analytics of Psychological Distress and Coping Among Fresh Migrant from North Eastern Region to Bengaluru City

Abstract
Psychological distress and coping are two aspects of the social and cognitive functioning of an individual. While the social environment enforces psychological distress, an individual uses his cognitive functions to create a mechanism of coping. This brings in a balance in individuals’ life, which enhances their individual and social functioning. The North Eastern part of India is well known for its deficits in the area of social, economic, instability in socio-political and lack of better education facilities in terms of professional courses which result in migration; in this process, a series of events are involved, and it has both positive and negative implication which often results in psychosocial issues. The current research is an effort to assess psychosocial issues confronting FMNER and their ways of coping. This research article discusses how data analytics for psychosocial distress and coping can be integrated among individuals migrating from one place to another place. The aim of the study is to assess the psychosocial perspective of FMNER to Bengaluru city with the following objective, to describe the socio-demographic profile and to study the psychosocial problem, psychological distress, and coping styles. Youth belonging from NER who is residing in Bengaluru city was considered for the study, the population of fresh migrants with less than one year stay and the age group of 18–34 years was considered, and sample size of 60 students, professionals, and non-professionals was selected for the study. Multistage random sampling was used. The tools for data collection used in the study are a semi-structured interview schedule, Self-Report questionnaire, and Brief COPE Data was analyzed using SPSS. The majority of respondents are in the age group of 21 and 23 years, there is an equal distribution of male and female 50%, and majority of respondents 46.7% educated up to HSSLC. Most of them 31.7% have stayed in Bangalore for the duration of 4 months, 60% know people in Bangalore prior to migration. 58.3% migrated for job purpose. Psychosocial issues like housing problems, difficulty to access health services, issues like the restriction of cooking of certain food, language difficulty, discrimination, and social profiling are being reported by respondents. SRQ clearly depicts that 73.5% were having a high level of psychological distress. The different styles of coping used often are instrumental support, Religion coping, and venting emotional support. The moderate coping styles are active coping and denial. The least is the substance used and humor. It is observed that male respondents have been using the substance as a way of coping. Thus, the overall findings of the current study show various issues and problems faced by the FMNER. The studies show the level of psychological distress is quite significant. The study provides scope for social work professionals to work in the area of preventive, promotive, and community mental health services and at the policy-making level to facilitate migration policy.
Dahunlyne Shylla, Daliboyina Muralidhar, Atiq Ahmed

Chapter 15. Security and Privacy Challenges for Big Data on Social Media

Abstract
In the current electronic age, users create vast and enormous data every second. As they upload photos, videos, online social conversations, etc., on social media and other platforms every day and every second, it is growing at exponential rates. Big Data is a new term given to huge datasets which is really hard to work on effectively. With the conventional data processing methods, it is difficult to process it. There are many challenges associated with Big Data. One of them is the technological challenge; that is dealing with the heavy data traffic which is being expanded daily by leaps and bounds. Capturing, storing, dissemination, analytics, and visualizations are the common problems of Big Data. Therefore, the computing infrastructure should be managed in such a way that can handle this Big Data. Another challenge is the sociological challenge; where this vast data is produced by various social networking companies like Facebook, Twitter, Google, and other mobile companies, Government agencies, etc.
Vineet Raj Singh Kushwah, Karunendra Verma

Chapter 16. Social Media: The Dark Horse of Market in Consumer Decision Journey

Abstract
With businesses continually striving to be insightful enough to precisely read the consumers’ desires and subjectively measure their satisfaction, the need for and impact of Big Data Analytics is growing without bounds. The chapter elucidates the proficiency of behavioral predictions enabled through the big data further made available by people on various social media platforms, which guide the marketers throughout the Consumer Decision Journey. These behavioral predictions help the businesses to keep tapping the consumer decision journey through several customer touch-points. Consequently, Big Data Analytics being a massive source of data collection drives marketers toward value creation by comprehending the needs of customers effectively and thus promoting value delivery to customers. With the help of various social media models, the chapter also unravels the benefits of behavioral predictions to not only marketers but also other researchers in the field of health, politics, academia, and so on focusing on personality traits, lifestyle and health of their subjects and not just their buying behavior. The chapter explores the various dimensions of social media platforms and models to demonstrate effective use of technically enhanced opportunities to drive customer satisfaction.
Nipun Dhaulta, Sakshi Aggarwal
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