Below are additional examples for my 2015 ACM/IEEE International Conference on Advances in Social Networks Analysis and Mining paper “Arguments and Interpretation in Big Social Data Analysis: A Survey of the ASONAM Community.”
B. Argumentation Theory and Research Design
The proposed framework for evaluation looks at research design, the strategic plan built by the researcher to coherently and logically organize the research process. An ideal research design provides a technical roadmap for the researcher to collect and analyze their data, and it also insures that the research addresses the problem successfully . To put this another way, the research design is the planned route to keep human errors from effecting the results. Components of most research designs include performing a literature review for other’s work on the topic, the proposal of research questions, the identification of data, a plan for collection and processing, and a method for analysis.
Big social data analysis complicates traditional notions of research design because the data exist independently of the research project and prior to the formulation of a research question. Due to this obstacle, I propose that we consider research designs as more than technical roadmaps: research designs are also arguments. By treating them as arguments, we can create standards for evaluation of components of the plan as propositions. The evaluation of research plans as arguments allows for the production of the best work possible by facilitating the explicit consideration of alternative explanations.
During the research process, there are numerous moments of interpretation where the researcher selects from a range of appropriate alternatives . In these moments, selecting the right or wrong answer over-simplifies the situation. The survey of ASONAM participants uncovers interpretive moments to evaluate them as arguments: while there is not a right or wrong answer, there are better answers that more completely or accurately address the problem space.
Argumentation theory provides a structure to understand how research designs function as arguments . Toulmin’s model for addressing formal arguments is composed of data, warrant, claim, ground, backing, and qualifier. Claims are the final conclusions, and warrants are what link data and the ground to a claim. The ground, which can often overlap with the data, is the basis for using a specific type of data. The ground is the definitions and theory where most arguments begin. The backing is additional support for an argument that bolsters unexpected or counter-intuitive claims. Finally, qualifiers condition when the claim should be accepted (e.g. “if x, then y”) or provide the strength of belief in its veracity (e.g. “sometimes x occurs”). These constituent parts can be found in big social data research designs, and by charting the arguments using this model, they can be evaluated and improved.
Fig. 1 is an example of the argumentation framework applied to the research design of Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8.
The backing for the ground—that collective mood states may impact systemic decisions— is italicized because it is a proposition that only logically supports the research plan after the technical demonstration of the model. The ground emerges from behavioral economics, borrowing strength from a well-established observational discipline. Ultimately, the technical aspects are sophisticated and performed without error and the qualifier maintains reasonable expectations for the results. In this case, the research as an argument is very persuasive to the community: It has been implemented in numerous real world applications and cited over 2,400 times.
Fig. 2: Chatterjee, A., & Perrizo, W. (2015, August). Classifying stocks using P-Trees and investor sentiment. In 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 1362-1367). IEEE.
The winners of RPI’s writing contest were announced last night, and I placed first in the graduate student essay category, winning $300, with my essay “Finding Rhetorical Agency in the Data Science Machine: Understanding Emerging Climate Change Arguments from Automated Data Modeling.”
Last year I came in second with my essay “The Path of Least Resistance: An exploration of non-human agency in a workplace survey.”
I am noticing a trend… despite having different contest judges both years, they appear to like papers that discuss technology and agency.
Congratulations to the other winners!
My latest post is now available over at cyborgology: http://thesocietypages.org/cyborgology/2015/11/05/how-do-we-talk-about-ethics-at-a-tech-conference/
Today, I joined my colleagues at Rensselaer and Dr. Debo Roy from the University of Aizu, Japan to participate in an ACM seminar on e-learning and technical communication. It was a strong and interesting mixture of technical and pedagogical discussions surrounding Legos in an ESL context, Classroom Assessment with new technologies, Information Design using CAD Software, Usability Testing of and classroom uses for 3D printing.
My talk was “Using CAD Software to Break from Photorealism in the Classroom: A Case Study of Build with Chrome and GIS Analytics.” More information is available here.
Hopefully our discussions will lead to an edited volume or special journal issue in the coming year.
The recording of my talk is available in 4 parts:
My January 2015 post on Cyborgology: Fact Check: Your Demand for Statistical Proof is Racist, has been added to the list of Statistical Literacy Papers, curated by Milo Schield, Editor for the Statistical Literacy Project.
The resources are expansive, and I am working my way through reading them now.
A new post came out this week over at Cyborogology on my personal experience with QS: http://thesocietypages.org/cyborgology/2015/05/05/the-hidden-anxieties-of-the-quantified-self-movement/
This summer, I worked as a graduate student intern at Time Inc. in New York City. When I got there, I was assigned to the IT department to pursue a 3 month research project on unstable user behavior, specifically in regards to reading habits and preference for digital versus print magazines. The governing provocation was how to get millennials to subscribe to digital products while simultaneously not alienating older generations of readers. Before undertaking the project, 3 months seemed too short from my academic experience, but this span is actually 4 or 5 times longer than Time Inc. spends on most background research projects dedicated to user experience during the product ideation process. Ideation here was the key– how does the company decide what digital products to build? Someone in the company (usually from one of the brands) has a great idea, asks a few people if they would use it, then persuades an executive it is a great idea. Shortly thereafter, the idea goes into the design and building stages. When these great ideas did not succeed in the marketplace, the secondary approach is to buy or build products that mimic other companies’ success: most recently this includes news aggregators (such as News 360) and digital magazine experiences (such as Flipboard). Unsurprisingly, the second approach usually places digital products behind the curve in an already saturated marketplace, while the first approach tends to produce products that are not appealing for a large group of consumers.
So what did I discover during my research? Many things… that I can’t share! This internship is also my first experience with proprietary information. But I can and will share some of the professional lessons I took away from the experience.
10 Things I Learned From My Internship at Time Inc:
1. Rebranding Hurdles: “Information Technology” versus “Technology and Product Engineering”
While I was there, Time Inc.’s IT department was rebranded as TaPE (Technology and Product Engineering). The goal was to more closely approximate the department’s role in the company and disassociate it away from the “less sexy” stereotypes of IT (watch The IT Crowd if you don’t know what that means). Turns out that rebranding takes a LOT of effort, and it isn’t as simple as making a new logo and masthead. I will be cautious about name and logo changes in the future because successfully associating the new appearance with a brand is a massive investment.
2. Value of Diverse Mentors
During the few months I was at Time, I had more mentors than I have ever had as an undergraduate or graduate student. These were people who would take a few minutes out of their busy day to answer a question I had or who would schedule meetings to talk about my progress. And it was fantastic. I received great advice from experts in their very specific fields and made long lasting connections. This article is spot on: The Benefits of Multiple Mentors. It makes me question the academic advisor- mentee relationship that places a single person as the driver behind a student’s career. Not only is that a significant amount of pressure on the advisor, as academics are increasingly tasked with larger workloads (administrative, service, research, and teaching), but it also doesn’t let the mentee take advantage of multiple areas of expertise. (Another good article on the topic from Tenure She Wrote.) My past experience with mentors/ advisors is also partially my own fault: I had a mental block to taking advantage of regular office hours unless I had a very specific question. Just going to chat with a professor always felt like I was wasting their time. My experience at Time helped me “get over” that view. If people are busy, the worst that will happen is they ask you to come back later. The only way to gather implicit and invaluable knowledge is to frequently talk to those in-the-know!
Last year (2013), I applied for the NSF GRFP program and didn’t get accepted (lots of sadness). However, it was a great learning experience for all the “how-to”s of grant applications and networking with other professionals interested in my area of study. I decided to post my application and reviews here for any other enterprising students who are applying this Fall– may you have better luck than I did!