Data is a thing that requires a source. There is something inherently pragmatic about having to choose a data source in particular fields. I constantly find this way of thinking separates philosophy from the natural sciences. In philosophy, one can simply appeal to rationality, logical structures that have been proven, or point to particular cases which have value to the author’s point, be it in this world or a “possible world.” There is no way to simply create observable data from ones own thoughts unless that person is a neuroscientist. This is not to say that scientists cannot use rationality or logical structures. Theories and methodologies develop specifically as logical ways to justify.
Data sources, it would appear, have a different history. Constrained with time, money, and resources, an academic is less tempted to seek out data sources that do not make themselves easily available. Perhaps one might say that some data comes out of necessity of the questions or hypotheses of theory, and in that case, it might be argued as possibly necessary in order to test particular theories, but even then, this seems to be rare in the social or information sciences.
This seems especially true when it comes to Internet studies and social media research. People rarely publish with extensive data on Facebook or Google Scholar for example, which is usually only accessible for large sums of money or corporate connections, and what can be seen is with minimal metadata. Instead, people turn to sites which lend themselves to ease of use. There are many kinds of ways in which one can gather Twitter data, and media from static websites such as Wikipedia, Reddit, and others can be scraped with a little experience with a xml scraping module in Python, PHP, or a similar language. Furthermore, with this, one can easily gather a significant amount of metadata in order to say much more than what the site says to the casual observer.
Data Tendencies & Considerations
If one sees the choice of data in this way, then there are some points that should be considered if one is to be self-critical. Firstly, it might not be much more difficult to find another data source, and this might be a major benefit to your potential readership. If Facebook data became somewhat more easy to access, one might should consider doing a Facebook study even if it is still more difficult than studying a different platform. Of course, this is dependent on the readership and the goals of research. However, simply studying Twitter, Reddit, and Wikipedia in order to understand, say, the political climate can be seriously detrimental especially at a time in which most people would argue that Facebook had a much bigger impact on votes. Certainly there are studies, but the difficulty with accepting these studies results are that they were largely funded or conducted by Facebook itself without any public release of data. Additionally, it makes it a little harder to accept the studies not on Facebook as having the most impact when it seems clear that the answers are on that platform or related to something about that platform’s design or users.
Secondly, one should consider the fragility of only studying one platform. If Twitter was gone tomorrow, could a research project speak about human behavior or information beyond Twitter? This seems to be something I have found fairly difficult with research areas largely organized around a single social platform. When I read a study that primarily focuses on a single platform, I find myself asking whether or not the work actually tells me something about people, information, or simply the platform itself. If it’s the latter, I always feel like I wasted my time. Considering the short period of time social media platforms historically have existed, speaking about the nature of a platform in of itself does not seem very appealing if that is not the goal.
Because of these two points, seems that attempting to consider possible studies on a different social network or platform is always a good idea. See if there are tools for lesser known platforms. See if there are ways to translate your technical skills and questions to your interests and that platform’s design. Certainly it is beneficial to study Twitter for certain questions and it helps that data is accessible. However, if one spends a little time to develop a new tool to understand another, perhaps this study will help bolster the generality of online social platform studies as a whole. It is really easy to simply use the tools you know, but being able to study elsewhere might be crucial for the future of the field.