Thursday, July 23, 2015

CFP: iConference 2016

If you're in a school of information, or if you're interested in information studies, consider attending this conference:
Dates: Sunday, March 20 through Wednesday, March 23, 2016
Location: Loew’s Philadelphia Hotel, Philadelphia, PA
Host: College of Computing & Informatics, Drexel University
They're now accepting submissions, with a deadline of September 9:

iConference 2016 takes place Sunday, March 20 through Wednesday, March 23, 2016, in historic Philadelphia, Pennsylvania, USA. This year’s theme of “Partnership with Society” examines the dynamic, evolving role of information science and today’s iSchool movement, and the benefits to society. The conference includes peer-reviewed PapersPostersWorkshopsSessions for Interaction and Engagement, and iSchools Doctoral Dissertation Award, all interspersed with multiple opportunities for networking. Early career and next generation researchers can engage in the Doctoral Student ColloquiumEarly Career Colloquium, and Undergraduate Student Showcase. 
Click here to view our Call for Participation and submission timeline.
Much more at the link.

Wednesday, July 22, 2015

Writing :: Co-creation by commenting

Jakobs, E.-M., Spinuzzi, C., Digmayer, C., & Pogue, G. (2015). Co-creation by commenting: Participatory ways to write Quicklook® reports. In Proceedings of IEEE professional communication society international professional communication conference (pp. 291–297). Limerick: IEEE.

Last year, my dear friend and colleague Eva Jakobs spent a few weeks in Austin. Among other things, we decided to collaborate on a small study of 24 Quicklook reports: technology assessment and commercialization reports used to determine whether a given innovation might have a chance of being valuable to specific stakeholders in a specific market. My colleagues at IC2 have an archive of such reports, and since Eva and her group are interested in revisions, versioning, and text mining, we agreed to provide an archive of drafts to her group.

The results were interesting. These reports are written by contracted business analysts who interview stakeholders and write a heavily templated report over approximately 40 hours. Then each report is sent to the program director, who typically comments on the draft and sends it back for revision. Usually the revision cycle involves just a few rounds, but some involve far more. (See the paper for details.) Eva's team was able to characterize these revisions.

But we also were able to (a) use the textual analysis to identify the sections where the comments most frequently occurred and (b) code the comments with an emergent coding scheme to identify their purposes (co-creation, argumentation, the writing process, and text quality). Based on this work, we were able to characterize the kinds of comments and identify how the parties synchronized expectations.

Eva was lead author; my contributions typically were supplemental.

For me, one of the most useful parts of this exercise was in scaling. My research has typically been in the qualitative case study mode: examining observations, interviews, and artifacts. And that mode does not scale well because the sheer amount of work is difficult to sustain. Text mining, on the other hand, scales quite well as long as one can ensure that the pattern matching means what you think it does. (Structure is not necessarily an indicator of meaning.) For this project, we were able to pair the two approaches, yielding an analysis that scaled up to a larger dataset while maintaining an interpretive analysis.

Writing :: How do entrepreneurs hone their pitches?

Spinuzzi, C., Pogue, G., Nelson, R. S., Thomson, K. S., Lorenzini, F., French, R. A., Burback, S., & Momberger, J. (2015). How do entrepreneurs hone their pitches? Analyzing how pitch presentations develop in a technology commercialization competition. In SIGDOC ’15: Proceedings of the 33rd ACM international conference on Design of communication (pp. 1–11). Limerick: ACM.
Here's another paper from our series on entrepreneurship -- and perhaps another useful lesson in writing.

My collaborators and I have been working on a monster paper that pulls together nine months' worth of qualitative data, covering a full cycle in a pitch competition. With the sheer amount of data available, the task has been daunting, and we have been distracted by quick wins. (I thought we would finish this paper a year earlier, frankly.) So how does one focus oneself on finishing such a large, unwieldy analysis?

One tactic is to break the analysis into small parts and set a deadline for each. And a great way to do that is to submit an abstract to a conference with conference proceedings. It focuses the mind quite effectively.

That's what we did here. I was dreading the task of watching, coding, and analyzing the videos in the pitch competition. So I did the following:

(a) I narrowed the scope of the task, selecting only four of the 25 pitches. The sampling was driven by (i) the available data (some participants declined and others had only partial data); (ii) the ultimate success (two of the selections went on to business development, two didn't); and (iii) type of innovation (I wanted to cover product, process, and principle).

(b) I submitted an abstract to SIGDOC in which I promised that our team would examine those presentations closely.

(c) I made good on that promise by closely analyzing the data. As I knew would happen, the data paraphrasing, coding, and analysis turned out to be fun.

(d) Based on the finished SIGDOC paper, I slotted the analysis of this segment into our monster manuscript.

Let's briefly talk about the word "I" above, because it points to the character of our collaboration. My collaborators collected most of the data and we all discussed how to characterize it. Ultimately, I put together the analysis and draft. Then I presented it to collaborators for an open review period, collecting valuable feedback that I folded back into the document. That's important: we chose to collaborate on a team in which each of us had different kinds of expertise, and although one of us might take the lead at different points, we had to make sure we could synchronize our expertise periodically. The paper was stronger for it.

And, again, the paper has become a building block for a much larger and more intimidating paper. For those readers who are tackling large-scale studies, this is key: break these into smaller tasks, preferably represented by smaller publications. Handling big projects this way has several advantages:

(1) You scope down the larger project and make it manageable.

(2) You get more publications (obviously). This might feel like cheating, but I argue that it's not -- it can be a crucial step, especially because ...

(3) You get periodic outside feedback on each step. For instance, the blind reviewers on this paper could have raised methodological concerns, which we could then address before rolling this segment into the larger paper. (They didn't in this case.)

Once you have assembled a building block like this one, you can cite it in the final paper, pointing people to further methodological details. And that brings me to one other thing.

I know there's a stigma against self-citation. But I have basically ignored it. In fact, I cite myself enough that people tease me about it at conferences. That's fine because I have a specific rationale for it.

Think about it in terms of putting together a coherent argument:

(1) When you write an article, you work on making it coherent through metadiscourse such as forecasting and through repeating certain information at key points in the manuscript. You have to make sure people know how the different parts fit into the larger argument.

(2) When you write a book or dissertation, you follow a similar strategy at a larger scale. For instance, you overview the argument in the introduction and recapitulate it in the conclusion. You establish transitions at the beginning and end of each chapter. And you drop in cross-references: "As we saw in chapter 3..."

(3) When you scale beyond a book to a body of publications that address parts of an overarching argument -- for instance, a set of articles on how innovators learn to be entrepreneurs -- you have to keep that multi-publication argument coherent too. One economical way is to cite your other publications on the same project.

Is that benefit of self-citation worth potential stigma? Weigh carefully, I guess.

Writing :: Understanding the value proposition as a cocreated claim

London, N., Pogue, G., & Spinuzzi, C. (2015). Understanding the value proposition as a cocreated claim. In Proceedings of IEEE professional communication society international professional communication conference (pp. 298–305). Limerick: IEEE.
This paper was part of a series of papers on entrepreneurship I've been writing along with partners at IC2 over the last two years. For this paper, we were interested in the notion of the value proposition, which is the claim of value to stakeholders. I was particularly interested in the value proposition because (a) it's a claim, and thus something rhetoricians should be able to address with our toolkit; (b) it sits at the intersection of two or more different activities, and is thus inherently a boundary-crossing claim.

It turns out that the value proposition has been generally underdefined and undertheorized in the relevant literature. One promising thread of literature has been Lusch and Vargo's discussion of Goods-Dominant Logic (which assumes that value resides in the good) vs. Service-Dominant Logic (which assumes that value comes from the service of providing the good). For this paper, we decided to explore the difference between the two, using five case studies in which the value proposition of a specific innovation was changed over time by the innovator.

The research itself was done by the lead author, Noelle London, who worked with Gregory Pogue (second author) and me over the course of a year. Noelle interviewed the business developers who mentored the innovators as well as examining innovator documents. (Noelle just finished her MA in Public Policy at the LBJ School here at UT, focusing on the Ecuadorean innovation ecosystem.) Greg and I provided feedback and extended the analysis. We're pretty happy with the resulting paper, although we already see points at which we can extend the analysis further.

In terms of writing, we each had things to contribute, and only by working together were we able to develop a strong finished piece. First, I developed a literature review of the GDL vs. SDL literature. Then Noelle abstracted the two perspectives so they could be contrasted, adding Lean Startup methodology for a third perspective to contrast. She worked closely with Greg to develop this line of thought, since Greg has vast experience in innovation and entrepreneurship. Based on this work, Noelle conducted the interviews, providing both the raw interviews and the assessment to us. I pulled the work together into a draft, essentially shaping it into the finished piece with frequent feedback from my two coauthors.

As I said, we already see points at which we would like to extend the analysis further. This paper is a step toward an expanded analysis, and we will perhaps take the next step soon, developing an article based on it. And that's perhaps the best takeaway for you, dear readers: each writing opportunity does not stand alone, it provides a step to the next one.