The Use of Data Science in Sociology

The Use of Data Science in Sociology Introduction Data analytics focuses on observing, understanding and making predictions of human behavior and other phenomena. It involves studying data in order to gain knowledge and make accurate deductions about the information. Data analytics increases the efficiency of processes by revealing patterns and information that would otherwise be challenging.

Sociology needs data science to facilitate better decision making and answer major questions pertaining to issues that affect the world. Despite significant evidence of the benefits derived from the application of data science to sociology, the proportion of data scientists in the field is lower than 10%.

As the use of data science continues to permeate other professions, there is an aspiration for sociologists to also apply data analytics in their field for two main reasons.

Firstly, there is a realization that data science has the potential of enhancing the subsections of sociology, and creating new topics of research due to the rapid advancement in data technologies. Secondly, the use of Big Data in sociology differs from mainstream sociology because it provides a more solid basis for data collection, and analysis, thus leading to the growth of sociology.

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Social sciences are changing due to advancements in the methods used in the collection and dissemination of data. Technological advancements have made it necessary for scientists and scholars to use more advanced data methods in order to draw more innovative decisions and outcomes hence leading to the application of big data in sociology (Salganik, 2019). Data analytics in sociology is important because it creates a better understanding of various concepts of sociology thus leading to positive changes in the field. Just as global problems have evolved with time, it is also important for the study of sociology to develop further; this has been achieved through data analytics.

The Impact of Data Analytics on Sociology Advances in data science have helped to diagnose social issues and also solve complex issues. In recent years, social science has incorporated big data analysis into its theories and methodologies, thus opening up a wide number of new topics for study. The integration of big data into sociology has also facilitated the development of qualitative and quantitative research. As a result, this makes the study of sociology more accurate and provides a basis upon which to observe and explain phenomena, and also make well-informed decisions. It enhanced social scientists’ ability to predict outcomes and also made complex processes and routines much easier to perform.

The importance of data science technologies in sociology was discovered several decades ago but only became widespread in the 21st century due to rapid advancements that made information technology more accessible. Before then, the costs of acquiring becoming tech-savvy was too high for most individuals and organizations, and big data was the preserve of universitis and wealthy organizations (Lauro, 2017). Thus, there were advancements in some organizations while others continued to use traditional methods of data analysis.

Additionally, the growth of the internet has made it possible to easily access data that before could only be obtained from a select few sources. The ease of generation and collection of data, accessibility of computers and software, as well as advancements in the field of statistics have led to the rapid growth of social sciences. This has led to major breakthroughs in social science, helping to pave the way for more growth in the future.

The Future of Data Analysis in Sociology It has become evident that there are numerous benefits to the use of data analysis to carefully select, sample, record and present data. Therefore, data analysis will continue to contribute significantly to social sciences in the future and will be used to answer more questions pertaining to social science. Due to data science, sociology today is more focused on observing and understanding behavior and trying to accurately predict future outcomes.

Data science will continue to provide numerous opportunities to solve problems in sociology.

Surveys and national statistics on various phenomena will be generated faster and more accurately, and it will be possible for social scientists to make accurate deductions, and better decisions as data becomes more easily accessible. Currently, less than 10% of data analysts work in the field of social sciences. Realizing the major gap in this industry, in future, this number will grow exponentially. Social science will widen as there will constantly be new areas of research to work on, and this will present opportunities for employment and growth in the field (Konopnski, 2013). There will also be many more areas of specialization in sociology.

Growth and advancements in social science will lead to new forms of data sets which will explore specific aspects of major social concerns such as similarities, differences, and underlying reasons for the occurrence of certain events. There is a bright and eventful future

for social science due to its integration with data analytics. Sociologists should therefore strive to actively engage with data analytics. As data analytics becomes more frequently used, there will be changes in government policies, as well as commercial and social practices.

There are five key roles of data analytics in organizations. These are; the first role is the data liaison. This role creates a link between the needs of an organization and the available areas where data science can be applied. The second role is the data architect; they have a thorough understanding of data technologies and create a link between the organization’s plans and how it can incorporate data. The third role is the platform architect. This individual works is the bridge between the sociology and analytics teams, and develops the infrastructure required to integrate analytics into social science. The fourth role is the data analyst. This individual performs the actual analysis of data and presents findings in a systematic manner to the organization’s stakeholders (Imai, 2018). The fifth role is the data scientist. In this role, the individual performs advanced data analysis, creates models of social science and translates data into actionable information. This role helps to make data more relevant and usable in an organization.

Of the five roles, the ones that are most common in social science are data analyst and data scientist since they are able to perform most of the other roles. Currently, there are very few data analysts in sociology, thus it is a highly marketable career for those who may choose to specialize their career. I am interested in pursuing my data analysis career in sociology because it is one of the careers that make a real change in humanity and society. I am interested in diagnosing the cause of societal problems and developing a lasting solution in order to restore justice where possible and alleviate people’s suffering. It is also a very

lucrative career with many opportunities for advancement since there are few analysts who have specialized their careers in sociology.

References Imai, K. (2018). Quantitative Social Science: An Introduction. Printeton University Press.

Konopinski, N. (2013). Doing Anthropological Research. Hoboken: Taylor and Francis.

Lauro, N. (2017). Data science and social research. Springer.

Pries, K., & Dunnigan, R. (2015). Big data analytics. Taylor & Francis.

Salganik, M. (2019). Bit by bit: Social Research in the Digital Age. Princeton University Press.