Yesterday I finished writing a full paper about the research tool LoopMe that I’ve been working on for six years now (see www.loopme.io). While LoopMe has been briefly described in a number of articles before, this was the first time I wrote a full paper about the research methodology underpinning LoopMe. The resulting paper can be downloaded here.
Disruptive advantages to entrepreneurship researchers
In research you often think by writing, and this was no exception. Writing the paper made me realize that LoopMe is one of the first examples ever of what I ended up labeling “Scientific Social Media” (abbreviated SSM). I defined SSM as social media platforms optimized for social science and used primarily for data collection and analysis. SSM combines important and complementary strengths of established research methods such as surveys and interviews. This facilitates the collection of large amounts of interconnected qualitative and quantitative data. SSM also allows for new possibilities to conduct longitudinal studies, to triangulate data and to analyze data in new and time efficient ways. These benefits imply that SSM could offer significant advantages to entrepreneurship researchers in terms of significantly lowering the cost of high quality data collection efforts, providing new-to-the-world data collection and analysis techniques and also bridging between qualitative and quantitative research. The new possibilities could be employed in many entrepreneurship related environments such as entrepreneurship and enterprise education, incubators, accelerators and other business start-up related environments. It could also be used to advance research in subfields such as venture capital, social entrepreneurship and intrapreneurship. Scholarly fields outside entrepreneurship could also use SSM to advance sociological research in diverse areas such as health, parenting, dieting, leadership and sustainability.
The writing process leading up to the article
The writing process started in late 2016 when I was asked by professor William Gartner to write a chapter about LoopMe in an upcoming Research Handbook he is working on. He wrote to me in December 2016, asking me to write a chapter to the method section, containing essentially what I wanted to say around LoopMe. The writing process started with an abstract to the 3E research conference, pitching a workshop around LoopMe for interested researchers. The workshop was delivered in May 2017 in Cork, spurring some enthusiasm among research colleagues. Next step in the writing process was in February 2017 when we were asked to describe LoopMe for a funding application to EU (which was later rejected). Eight pages were thrown together quite quickly. The bulk of the writing process happened in April to June. I then realized that LoopMe was an example of using social media for research in social science.
An emerging new research field applying digital methods
Now an entire new field of literature had to be reviewed, the emerging field of “Computational Social Science”, or “Digital Sociology”, or “Virtual Ethnography”. An emerging field with many names. But most studies that they wrote about had so far been focused on using data from established social media platforms such as Facebook and Twitter. This technique indeed has a number of shortcomings. The most important one is perhaps that you need to go on a fishing trip in a sea of data and see what research questions pop up. This is contrary to what has been recommended by many method scholars.
One of the first attempts at not doing social media research backwards
I then realized that our group of researchers and programmers behind LoopMe were among the first ones to start with a research question, then building a social media platform tailored for generating answers to that question. The question was: “How do people develop their entrepreneurial competencies?”. The work has so far generated a lot of articles that you can find here. From a method point of view, LoopMe thus turned out to be perhaps the first social media platform in the world built around a research question (or research program). Most social media platforms are instead built for the purpose of making money. If you want to do research around the data that such a platform generates, you will be quite limited in what questions you can answer. This can be seen in much of the work out there. Fantastic and exciting new methods are applied, but in order to answer rather dull research questions. There are of course exceptions. But still, I could not get away the feeling that most research in this field was done backwards. First a sea of data was picked, then people started fishing relentlessly. I’ve been taught to avoid that approach in my PhD studies. But perhaps it is natural in an emerging methodological field to experiment with what is out there.
Combining strengths of interviews and surveys
One of the most intriguing things that came out of the writing process was a table contrasting SSM to the two most common data collection methods in my field – interviews and surveys. I think it is quite interesting to see how SSM manages to combine most of the strengths of both interviews and surveys, and at the same time mitigate many of the weaknesses of both methods. Now that is quite cool, isn’t it? See the table below here:
Your feedback, please!
While I now have a full paper on LoopMe for the first time since the journey started, it is not fully ready. It will be revised in autumn after I have received feedback from the editors. I would also love to get your feedback on it. I have until December 2017 to improve the paper. So download my paper and see what you think, and then let me know by dropping me an e-mail. Thanks!