Digital Trace Data in Communication

Digital Trace Data in Communication and Social Computing Research The purpose of this article is to enhance the design and research in social media networks by better developing technological actions such as interface design, behavior modeling, and system building with understanding of social characteristics as indicated by social technology concepts. In particular, the author seeks to show that individuals leave traces of their activities when interacting with digital devices.

This foreshadows the present research and practical interest in "big data." Most of the work revolves on how to derive significance from these traces (Freelon, 2014). Prior research on which the study is based Prior research was based on social uses of trace data and the failure to adapt social reminiscing. Researchers found that choices around consuming, creating, and delegating data in social media platforms are complex. This is because individuals simultaneously manage concerns around relationship dynamics, identity management, and visibility of activity to self-arching and third parties.

Key points or findings this article presents The article supports individual reflection and reminiscence. These are key psychological processes for all age groups. Key Insights from the article are that data people accumulate in social media networks can support personal reflection and social reminiscence. The significance of the study The article is significant because it draws a difference between two forms of big trace data sets: vertical and horizontal. This helps in addressing practical and conceptual challenges confronted by computational social science and expands toolkit for digital ethnographers.

Ethnographic researchers rely on participant observation and use trace data sets as observational data. Thus, both vertical and horizontal data analysis presented in the article are crucial to understand digital traces in a better way (Freelon, 2014). Methods the author(s) used to conduct this study. Since the author has used to trace data, it concentrates primarily on participation traces, rather than other types of transactional information, such as location data from mobile phones and web browsing logs.

This cannot be considered as the author's omission: it shows a lack of published ethnographic studies that use transactional information as a technique of observation. However, this has led to a narrow interpretation of observations, involving watching images and texts on a computer screen rather than watching people in offline environments. As an ethnographer, the author has routinely gathered information in-person that is quite similar to machine-collected transactional information (Freelon, 2014).

5) Do the authors present recommendations for future research and studies that build on the topics addressed in this article? Yes, the author has presented recommendations for future research on the topic addressed in this article. He recommends that more data are not useful to educational scientists or policy makers, unless they are examined and modified to generate knowledge and information.

Knowing the variations between kinds of trace data, and how they correspond with techniques of analysis should be the first step toward creating kinds of analysis that maximize on the features of these new data sets. Future studies on this topic must integrate qualitative techniques to observational information.