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Digital By Product Data in the Social Sciences - Literature review Example

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This literature review "Digital By Product Data in the Social Sciences" presents social science researchers that are increasingly turning to studies that analyze digital by-product data in order to provide useful new conclusions about the social phenomenon important to us around the globe…
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Digital By Product Data in the Social Sciences
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Digital By Product Data in the Social Sciences 0 Introduction Data, statistics, and other forms of empirical evidence are only truly as useful in as much as they are understood. The best information, without a proper foundation, is actually quite useless and can end up forming the basis for false conclusions, particularly in the social science. This can be represented in a study of digital by product data. It can be said that such data must first be completely understood before the information can even begin to be useful to social researchers. Quite simply, digital by product data involves information that is collected by reviewing Internet operating systems and the data that is included in a system to back-up content that is located there (Adkins & Lury, 2009). This can included a users Internet browser history, the files that have been downloaded, photos uploaded to the computer, and a host of other data that is a by product of actually using the computer or Internet. The prevailing theory in this area is that much of society is becoming digitized and individuals are increasingly living their lives with full technological capabilities to the extent that their very being can be captured digitally (Adkins & Lury, 2009). With daily live becoming increasingly defined by our digital activity, it only stands to reason that social scientists would be interested in digital by product data. Such information, however, is typically gleaned from the records of various pieces of technology and not from direct interaction with human participants in research. As such, it is imperative to first understand the context of any such by product data before any reliable conclusions can actually be drawn from it. Conversely, this digital by product data, once properly understood, actually contains a wealth of information not previously available to social scientists under most conditions. In fact, digital by product data is, “An important opportunity to help social scientists overcome various bottlenecks such as the deficiency of data and the limitations of analysis and possible risks of bias when using existing research methodology” (Beer, 2008, p. 622). More traditional forms of sociological research, for example, tends to focus on direct human response and interaction regarding the phenomenon being studied. While this is obviously effective at determining societal trends, there are a variety of external factors and influences that can skew the data being collected and analysed. Digital by product data, however, can serve to eliminate these factors by providing real information that is largely free from user and participant bias. In the modern era, digital by product data is being used to analyse information about individuals contained online, via their various activities, in an effort to explore social and cultural phenomenon and any differences that might be occurring in the global community. In order to accomplish this objective, however, social science researchers must carefully consider the types of data and their sources that will prove useful in the collection of such information. In addition, the usefulness of the actual topic being studied must be carefully weight in order to ascertain whether or not the studying of the digital by product data will prove a more useful methodology than more traditional quantitative or qualitative based studies (Munt, 2008). It is recommended, therefore, that such data be collected and analysed in a step by step sequential manner in order to design a collaborative model that determines important conclusions to the topic being studied (Back & Puwar 2012). In answering the question that forms the basis for this particular study, data collected from the digital realm of our lives must first be understand before its usefulness can truly be realised. If this can be accomplished, it has been shown that the use of digital by product data by social scientist can certain result in a host of benefits that can be used to resolve certain challenges that have existed in the discipline by incorporating other methodologies into a research study. Back & Puwar (2012) postulate that, “Such an evaluation can help scholars interested in using digital by-product data in their studies and also can provide some innovative ideas for social scientists in a new information age” (p. 11). With this in mind, this report will generate a plausible way of answering this important question of the importance in understanding digital by-product data before it can be proven useful to social scientists. This will be accomplished primarily by reviewing current literature available in this field and combining that with actual examples of how digital by-product can prove beneficial to studies conducted by social scientists moving forward. 2. Literature Review There are certainly methodological challenges facing researchers in the various disciplines of the social sciences in this age of the Internet and ready access to digital technology. In fact, daily lives are now becoming increasingly reliant on digital technologies to the point that the basis for many decisions can be found online and in full purview of other members of society (Back 2007). The digital age has now been dubbed with the term ‘virtual life’ and forms a hidden reality that is not, as of yet, fully understood by social science researchers. In fact, much of the digital by-product data available today reveals a reality that is contrary to more traditional definitions and understandings of society, so it can be said that our very reality is gradually being rewritten by this digital age. The Internet, and other various forms of technology, have modernised our life style, altered the way we communicate with one another, is has even been attributed to certain social and psychological changes in existence today (Boyd & Crawford 2012). This virtual transformation of the lifestyle exhibited by the billions alive today have dramatically altered the methods by which social scientists can employ to ascertain social phenomenon. Innovative and modern information and communication technologies being deployed today have enabled a variety of new research topics and studies to be conducted as individuals today now have a global sense of identity and are less reliant on geographical boundaries. In addition, such technology and digital media is opening up a whole new arena in terms of self-expression, and has served to expand the social network of people beyond any comprehension imaginable a mere decade ago (Renwick 2012). As a result of this recent information, social scientists today have become increase interested in exploring how individuals are using digital media, primarily in the form of the Internet, to interact with one another in ways not previously seen in society. These interactions have created a whole host of new social issues simply because of the development of the Internet and, moving forward, it would be beneficial to understand how the digitisation of society and culture is changing the very fabric of who we are as a global community. Social scientists have begun to study these issues by examining digital by-product data, but before they can draw reliable conclusions, they must certainly first understand what this data truly entails and means. Deciphering through the mounds of interaction and communication that takes place daily on the Internet and via other digital means is no easy task to be sure (Boyd & Crawford 2012). While the emergence of digital by-product has created a plethora of new topics for social science researchers to study and analyse, it has also resulted in the need to develop new methodologies and process by which such data can be efficiently and effectively discussed. Only upon doing so can reasonable and plausible conclusions that benefit larger society truly be actualised. A current review of existing literature in this area reveals that social science researcher are still looking for ways to better analyse digital by-product data, primary be through the development of a new type of methodology that would enable them to better understand the information uncovered (Burawoy 2005). Without such an understanding, any such undertaking would basically be useless as conclusion would be drawn on misinterpretations of the collected data. This appears to be further complicated by the reality that the technology we are talking about here is continually evolving and constantly changing itself. This means that it is quite possible methodologies developed today to analyse digital by-product data my be outdated by the time any significant studies in new areas of social science are conducted (Chow 2008). These obstacles are no insurmountable, however, and social scientists are learning to adapt to this new global technology revolution and are hopeful to develop effective solutions that will better inform the public about trends and modern developments in a host of social science endeavours. The emergence of new technologies in information and communication is apparent in many areas of society. Consider the development of social networks on the Internet. This relatively new phenomenon is redeveloping the way humans interact with one another, and much can be gleaned about an individual simply by examining the digital by-product data that is located on such networks (Latour 2010). Rather than spending countless research hours developing an exhaustive account of a person’s associations, for example, the data contained on social network can be scrutinised to determine connections between individuals, how people interact with one another, who they choose to associate with, and how open they are with certain types and groups of individuals. All of this can be studied without the need for exhaustive interviews or surveys, the data from which is often biased and skewed, and be triangulated with information uncovered from other sources as well (Das 2006). Consider the ramifications of studying group dynamics and behaviours. Rather than approaching groups and looking for ways to speak with and draw conclusions about individual members, social networks can be examined to study these groups themselves. The individuals that associate with those groups can be ascertained from the digital by-product data that is collected, and that can be correlated with information uncovered through an analysis of each individual member within that group (Crang & Grahm 2007). In addition, social networks located on the Internet provide social science researchers with a pyramid structure of know relationships that keeps expanding out. Friends of friends can be located quite quickly, and data about them can then be compared with data found elsewhere to draw important inferences about how social behaviour is changing during this age of technology and expanding globally connected relationships. Of course, there are issues of ethics and morality in examining such data, similar to that of other research methodologies, and the research himself must be able to not only understand the data, but develop ways of drawing meaningful inferences from what is discovered (Crang & Grahm 2007). The Internet is changing our cultural communication as well. This technology is bridging the gap traditionally found amongst the different people groups of the world, gradually creating a globally interconnected community whereby cultural lines and boundaries are often blurred. Much of this can be uncovered from digital by-product data contained on the Internet. We are communicating with others around the globe on a scale and scope never before thought possible. Innovations in communication have made it possible to make friends across borders, tapping into another social network altogether. This create multiple opportunities for further research by those the field of social science as any one individual might now belong to separate and distinct social groups, causing them to exhibit different behaviours depending on which group they are in at any given moment in time (Connerton 2009). This type of information would be difficult, if not impossible, to ascertain using traditional research methodologies as such techniques typically focus on particular components of an individual’s life. Digital by-product data, however, can open up multiple perspectives on a topic by utilising the Internet as a primary means of information gathering (Strathern 2004). The challenges presented herein, therefore, is how to create a new methodology in the social sciences to be able to effective conduct and complete studies where digital by-product data is collected almost exclusively from sources found on the Internet. To be sure, for quite some time, social science researchers have utilised the Internet as a way to communicate with participants within the parameters of traditional sampling method commonly accepted by professional in the field. In fact, as social science researchers have begun to adapt to using the Internet as a means to discover more about certain social phenomenon of interest to them, they have also been able to attract more respondents that are willing to participate in such studies (Savage & Burrows 2007). In addition, the advent of certain information and communication technologies have simplified the process by which social science researchers themselves can talk to one another, share ideas, and format theories and conclusion based on the digital by-product data tat has been collect in any given area. This has also opened up geographical borders to accomplish this task, as social science researchers no longer need to depend on scholarly journals to learn about important work being conducted the word; they are able to conduct the researcher directly, often in real time, to discuss their findings and draw correlations to their own studies (Savage 2010). As a result of this, traditional research methodologies are beginning to be merged with modern innovation to make use of the Internet and all of the data that available and waiting to be analysed. In considering how to conduct social science research projects using digital by-product data, many scholars have actually expressed concern over the limitations of relying too heavily on more traditional research methodologies. While acknowledging that reality that such strategies are useful in many research endeavours, the information to be gleaned from Internet communication is much more rich and detailed that such methodologies are really equipped to deal with (Savage 2009). This is particularly when considering the many topics in the field of social have recently seen many social and cultural developments in recent years, primarily as a result of the increased availability and use of digital technology, to the point that must qualitative and quantitative research becomes outdated before researchers even have the opportunity to publish their findings. At the same time, there are some topics that still necessitate the use of surveys and in-depth personal interviews. Consider a study on women in prison. It would be difficult to discount the value of traditional research methodologies when studying this particular population. For one, digital by-product data on women who are incarcerated would be severely limited in scope. In addition, the value of personal interviews with this population cannot be discounted, as verbal and facial interaction often paints a much different picture than one could ascertain simply looking at online data. When it comes to personal interaction with participants, there really is no substitute for actual real life interaction with the researcher (Said 2012). This type of methodology does certainly afford the researcher with the opportunity to ask more probing questions based on comments made by the participant, in addition to allowing them to control the environment in which the interview takes place as well as noting down any external observations that might be useful within the context of the study. On the hand, as we have discussed, there are many biases that exist in the more traditional social science research methodologies that the analysing of digital by-product data can work to overcome. While participants can mask their true feelings and opinions in a survey or interview type setting, this becomes much more difficult to accomplish with such electronic data (Ritzer & Jurgenson 2010). This is perhaps a primary reason why researchers in the social sciences are becoming increasingly interested in developing sound methodologies that enable them to accurately and efficiently examine digital by-product data in such a manner as to expand on previously existing research. The issue here goes back to understanding the nature of by-product data that is digitised. If this could be done effectively by traditional means, then social science researchers would most certainly employ their use, thereby enabling to better comprehend and dissect the information discovered regarding a particular social phenomenon. This, however, is frequently not the case with Internet related data. To illustrate this point, consider three of the most commonly employed methodologies in social science when working on the Internet. They include the email-based survey, an Internet based questionnaire, and an online and in-depth interview. Each of these strategies contain various flaws that have been mentioned by social science researcher. At the basic level, this begins with a low response rate that results from distributing any type of survey online (Beer 2008). In addition, many participants simply ignore the surveys they are sent, making it extremely difficult to gather enough information to draw meaningful and reliable conclusions. In order to better understand the digital by-product data that is available on the Internet it does seem necessary to consider the reality that traditional sampling techniques are simply in adequate when looking at social phenomenon primarily from a digital perspective. To being such an endeavour as we are discussing, researchers in the social sciences must aim to identify data available on the Internet that is, as of yet, unused. This comes in different forms, and cannot always be ascertained by simply deploying online surveys and interviews. It behooves those in the field, therefore, to begin implement alternative methodologies, via available Internet applications as an example, that are designed to not only collect the digital by-product data, but help to interpret and analyse it as well. If this can accomplished, it is certainly possible to use data found on the Internet to satisfy the needs of social science researchers interested in studying new social phenomenon, all because of the adoption of new methodological perspectives and theories. One of the issues in drawing conclusions from Internet based research lies in trying to determine the causes of illustrated behaviour (Latour 2010). While the Internet has certainly expanded the myriad of options available globally to communicate with one another, this complexity of social interaction has created great difficulty for social science researchers in determining what the digital data collected actually means in the large context of the social phenomenon being examined. New technology is currently being developed, however, that will alter the methods by which researchers in the social sciences explore new data and the approaches they use to generate conclusions based on the information that is gathered. One way that this shift in social science research methods is happening is reflected in a change being implemented by researchers to focus more on Internet-related topics and social concepts, many of which have been newly developed in recent years and are growing in popularity exponentially. Consider Facebook and Twitter as to obvious examples. The amount of digital by-product data available on these two sites alone is staggering. Social science researchers can quite easily develop a methodology by which they approach multiple participants that span the globe in an attempt to study a particular topic or area of interest. This leads into a discussion of a second area of change in methodology, which is reflected in the way that Internet and Communication technology related devices and options have served to speed up the manner in which we communicate with one another, in addition to expanding the number of options available to us to actually conduct such communication in the first place. Using traditional sampling methods to obtain data, the expense and time involved in gathering data alone often precluded many studies from taking place (Connerton 2009). With the advance of newly digitised data in the form of the Internet, however, this obstacle is been minimised. In addition, the manner by which global citizens communicate with one another today across borders also benefits social science researchers as well. No longer does a researcher have to be physically present within the geographical area of the population being studied, as they can now use various communication tools available on the Internet to tap into a participant base that is constantly expanding and broadening its scope. The current process by which available data is being digitised today is also provide great assistance to social science researchers in their efforts to develop a mechanism by which information can be better organised, analysed, and compared with previous findings. One of the complexities in understanding digital by-product data is also evident in the speed with which the Internet produces and assimilates information on a constant basis. It is often beyond comprehension to digest the sheer volume and complexity of data available electronically, and this continue to increase exponentially as time goes on. At the same, these data transactions, as they occur in real time, can provide a vast array of information that proves extremely useful to the researcher. Of course, the trick is being able to not only gain timely access to this data, but to be able to understand and analyse as it comes in. All of this must be done quickly so that critical information is not only caught, but is understood before certain social phenomenon and available data shifts once again. The advantages of such Internet and communication based technology systems for the researcher, then, are countless. In order to better understand just how this information can and is proving useful in many research endeavours, one must consider various sampling method associated with data collection and analysis (Back & Puwar 2012). The methods are changing the way in which research is being conducted, and they are certain leading to both a practical and methodological shift in perspective as new topics are being discussed via digital communication means. To illustrate this further, let us first consider Internet-based sampling methods. Recent studies analysing how society have radically changed with advancing technology has fuelled the conversation revolving around digital by-product data. At the current time, it appears that most researchers in the social sciences have opted to go a more conventional and conservative route in conducting Internet based research. This seems to mean that many practitioners are making use of new digital technology as a resource to conduct field observations and to obtain relevant data. Research in the social sciences that uses the Internet as its primary information gathering source depends on the analysis and discovery of relationships, interaction, and social based characteristics (Connerton 2009). In the early days of conducting research in this area, it was quickly discovered that there were inherent limitations in the methodological approach taken by many researchers in adopting certain Internet related sampling strategies and techniques. In order to properly understand digital by-product data, however, a new methodology had to be created. This needed to be one that would likely merge the traditional methods that social science researchers employed in gathering data, with the complexity of attaining and analysing digital data gathered online. The creation of such a methodology now enables researcher to deal with a far more diverse range of research topics that was ever logistically possible before. The Internet is now consider a primary mechanism by which social science research is to be conducted, which makes the question of how to better understand digital by-product data all the more important. To consider this point, it is beneficial to consider how the Internet is being used today as a primary tool to complete a set sampling survey in most areas of social science research. The Internet itself consists of a myriad of multimedia functions that allows study participants and researchers to communicate quickly and with relative ease. By utilising email and websites, just to name a couple of the mediums employed by social science researchers today, sample participants are not only more easily recruited into a study, but are assimilated into target groups that are of particular interest within the scope of the social phenomenon being observed. 3.0 Conclusion Data, statistics, and other forms of empirical evidence are only truly as useful in as much as they are understood. The best information, without a proper foundation, is actually quite useless and can end up forming the basis for false conclusions, particularly in the social science. This can be represented in a study of digital by product data. It can be said that such data must first be completely understood before the information can even begin to be useful to social researchers. Quite simply, digital by product data involves information that is collected by reviewing Internet operating systems and the data that is included in a system to back-up content that is located there (Adkins & Lury, 2009). This can included a users Internet browser history, the files that have been downloaded, photos uploaded to the computer, and a host of other data that is a by product of actually using the computer or Internet. The prevailing theory in this area is that much of society is becoming digitized and individuals are increasingly living their lives with full technological capabilities to the extent that their very being can be captured digitally (Adkins & Lury, 2009). As we conclude, let us quickly examine the two most commonly deployed sampling methods for dissecting and understanding digital by-product data. Methods utilising the Internet, first off, allow researchers to generate data from population samples much more quickly than traditional paper based survey or in-person interviews. In addition, scientific surveys administered on the Internet allows practitioners in a given field to reach a broad and often global audience, at a fraction of the cost. This is a critical point, as much social research is conducted with limited to no budget. Naturally, one does have to contend with the reality that such a methodology does not allow the researcher to put a face to the responses, so it is hard to predict whether or not any given participant responded truthfully, or if they submitted answers that were steeped in bias. To compensate for this, Internet based sampling methods typically have an extremely high sample size in order to make such responses statistically insignificant. This does tend to magnify the amount of data that one must go through in order to arrive at plausible conclusions, but once that difficulty is overcome then the topics that can be further studied become rich. Such a methodology also enables digital data, information, and instructions to be quickly delivered to all participants in a study, thereby dramatically decreasing the amount of time it takes to complete the actual sampling itself. Surveys administered via email are also increasingly becoming popular amongst researchers in the social sciences. In reality, however, this is simply a new way of conducting traditional paper surveys. Certainly the time and expense in conducting such surveys is dramatically reduced under such a scenario, but this does little to help the researcher uncover the meaning behind digital by-product data. In the end, social science researchers are increasingly turning to studies that analyse digital by-product data in order to provide useful new conclusions about the social phenomenon important to us around the globe. This necessitates a new methodology that not only allows researchers the opportunity to gather such valuable data located online, but to effectively and efficiently analyse it. Without the latter, the data is useless, which is the basis for this question. To understand such digital by-product data, social science researchers will continue to merge traditional methodologies with more modern sampling strategies all aimed at better streamlining the overall research process in this age of modernity. References Adkins, L. and Lury, L. (2009). What is the empirical. European Journal of Social Theory, 12, 5-20. Back, L. and Puwar, N. (2012). A manifesto for live methods: Provocations and capacities. The Sociological Review, 60(S1), 6-17. Back, L. (2007). The Art of Listening. Oxford: Berg. Beer, D. (2008). Researching a confessional society. International Journal of Market Research, 50(5), 619-629. Boyd, D. and Crawford, K. (2012). Critical questions for big data. Information, Communication, and Society, 15(5), 662-679. Burawoy, M. (2005). For public sociology. American Sociological Review, 70(1), 4-28. Chow, R. (2008). Ethics after idealism. Bloomington, IN: Indiana University Press. Connerton, P. (2009). How modernity forgets. Cambridge: University of Cambridge Press. Crang, M. and Graham, S. (2007). Sentient cities ambient intelligence and the politics of urban space. Information, Communication, and Society, 10(6), 789-817. Das, V. (2006). Life and Words. Berkeley, CA: University of California Press. Latour, B. (2010). An attempt at a compositionist manifesto. New Literary History, 41, 471-490. Munt, S. (2008). Heroic desire: Lesbian identity and cultural space. New York: New York University Press. Murthy, D. (2008). Digital ethnography: An examination of the use of new technologies in social research. Sociology, 42(5), 837-855. Renwick, C. (2012). British Sociology’s Lost Biological Roots: A History of Futures Past. Basigngstoke: Palgrave Macmillan. Ritzer, G. and Jurgenson, N. (2010). Production, consumption, and presumption. Journal of Consumer Culture, 10(1), 13-36. Said, E. (2012). The public role of writers and intellectuals. The Public Intellectual, 19-39, Oxford: Blackwell. Savage, M. (2009). Contemporary sociology and the challenger of descriptive assemblage. European Journal of Social Theory, 12(1), 155-174. Savage, M. (2010). Identities and social change in Britain since 1940: The politics of method.Oxford: Oxford University Press. Savage, M. and Burrows, R. (2007). The coming crisis of empirical sociology, 41(5), 885-899. Strathern, M. (2004). Commons and borderlands. Wantage: Sean Kingston. Read More
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