Dissertation Survey: Arguments and Interpretation in Big Social Data Analysis


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After passing my Prospectus Defense in December, my PhD project was suddenly real: I must now actually do primary research and write a several hundred page document. The best advice I have gotten so far is to take it one step at a time. So here is a progress report on Stage 1: The Survey.

I submitted my survey text to Rensselaer’s Institutional Review Board in January and received an exemption: “45CFR46.101(b)(2): Anonymous Surveys – No Risk”. Since my survey is anonymous and does not harm any of the respondents, I am cleared for action.

My target community is big social data researchers in the United States working out of academic institutions. For the first round of invitations, I have been using the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining proceedings to solicit respondents. Everyone has been very polite and interested in my work, and I have had a solid 20% response rate. My goal is to get at least 20 responses, but I will continue collecting through the end of March.

For this initial survey, I am interested in how data scientists use interpretation to complete their projects and how they communicate their results to their audience. My survey questions focus on a few key themes. First, I was interested in how respondents understood their disciplinary role and why they became interested in big social data. Next, I asked about interpretation: how they decided on research questions and generated explanations for their results. If they changed their research questions mid-way through the analysis, I also wanted to know what steps they took to ensure accuracy. Then, I turned to technical aspects of the process, asking what steps they took and how they handled false-negative and false-positives. Finally, I asked about communicating results persuasively and to a target audience. The preliminary results look promising, and I personally find them fascinating!

In case anyone is particularly interested, here are the exact questions. The bulk of them are directed at the researcher’s specific project they submitted to the ASONAM conference. Continue reading


The Hidden Anxieties of Self-Tracking

Radio Interview with Nora Young, Spark, CBC Radio

Many of us willingly collect data about ourselves through wearable trackers or apps with the hope that through measuring and charting our life, we can actually control it. But sometimes the very effort of trying to control it causes anxiety.

Researcher Candice Lanius talks about what she calls the “hidden anxieties” of the quantified self movement.

Finding Agency in the Data Science Machine: Understanding Emerging Climate Change Arguments from Automated Data Modeling


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National Communication Association Pre-Conference on Agency in Honor of Carolyn R. Miller. Las Vegas, Nevada, November 18, 2015.

Panel: Automation and Agency

Author: Candice Lanius, Rensselaer Polytechnic Institute, PhD Student in Dept of Communication & Media

Title: Finding Agency in the Data Science Machine: Understanding Emerging Climate Change Arguments from Automated Data Modeling

Abstract: Carolyn Miller’s piece “What can automation tell us about agency?” is groundbreaking for its contribution to understanding agency and responsibility when humans rely on automated systems. Miller’s insights are increasingly relevant in the context of data science, a new field that has expanded rapidly over the course of five years. In data science, particularly “big data”, much of the analytical process is beyond the conceptual power of human agents, so interpretation and processing has become automated. Miller’s conceptualization of agency as a property of the event (analytic process), not something found exclusively in human analysts, opens a door to important questions about the algorithm and code’s role in constructing arguments about human behavior in conjunction with the analyst. In one of the greatest challenges facing humanity today—climate change—modeling the interaction between human behavior and the environment is foundational to understanding and intervening. I will use Miller’s contribution for understanding agency to investigate the ideology and rhetorical impact of a series of big data projects: Google’s Earth Engine, Microsoft Research’s Madingley Model, and Data.gov’s Climate data resource. Each of these projects automates their inquiries in distinct ways to address the climate change crisis, and it is important to understand what the rhetorical and political implications of automation are for the global community.

[PDF Version] Finding Agency in the Data Science Machine

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ACM Chapter Seminar on E-Learning and Technical Communication


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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:

Rhetoric Society of America 2015 Summer Institute – What is data? A rhetorical analysis of born-digital social data.


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On June 5th-7th, I attended the workshop portion of the Rhetoric Society of America’s biennial summer institute at the University of Wisconsin-Madison. (Finally got to use that Dept. Rhetorical Travel Award I won last August!)

The workshop I attended, Rhetoric’s Algorithms, was hosted by Dr. Jim Brown (Rutgers University) and Annette Vee (University of Pittsburgh). They described the workshop as:

More than just tools to produce text, image, or sound, computational procedures are persuasive and expressive. In this workshop, we’ll dive deeper into the machine: We’ll consider the rhetoric of computation by examining code itself as rhetorical. By annexing code into rhetoric, we can reconsider both the rhetorical possibilities of algorithms and the algorithmic possibilities of language production and persuasion. Thus, in this workshop we will aim to see how both rhetoric and computation change in light of the other. Given the ever-expanding role of digital computers in our various rhetorical ecologies, it is essential that rhetoricians build theoretical tools for grappling with computation’s various rhetorical dimensions. The workshop will take up emerging work in rhetorical theory that addresses computation (including a forthcoming special issue of Computational Culture edited by the workshop leaders). However, attendees will also undertake algorithmic re-readings of foundational rhetorical texts.

The workshop was a great networking experience. The group was evenly divided between individuals interested in rhetoric as machinic/ process/ algorithm and those (like myself) who are interested in computation/ algorithms as rhetorical. To introduce our work, each participant prepared a short 20 slides X 20 second presentation. Mine was “What is data?” and looked at the substance of born-digital, found, social data that is commonly used in big social analytic applications (that presentation is included below).

While I am happy I attended the workshop, I did find myself wishing we had discussed scale and contemporary technology more. As a hands on workshop, we did tinkering exercises throughout with early computer programs (such as Stachey’s Love Letter Generator), and that was a lot of fun and showed us the value of opening up the “black box” for creative exploration/ learning. However, the tinkering was an exercise with small machines and the concepts we discussed were largely attached to this level of analysis. I frequently asked, if our technologies and tools are scaling upwards, how should our rhetorical concepts change to scale up as well? I am glad RSA is beginning to pay attention to computation and rhetoric (another workshop led by Collin Gifford Brooke discussed Rhetorics and Networks), yet I still feel the discipline is behind the curve by at least a decade.

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