Wiki language research

Project management wiki for Darren, Jim (and Aaron's) cultural peer production research.

Action Items

eliminate bots from sample
find percent change for talk edits at median values of coefs for each language.

Undergrads

Bennett

continue hand-coding samples
take notes on interesting patters (in notes document on spreadsheets)
note if names of bots are included in "list of bots"

Summer Schedule

Week 1: Write initial analysis, get google doc - latex pipeline setup
Week 2-3: Flag bot edits, pull new samples for coding based on updated percentiles, write new draft of analysis
Week 3-6: Develop hypotheses and run analysis
- Cross cultural deliberative practices
- Discussion structure
- Something else?
- more qualitative coding + bot spot checks
Week 7-CHI Deadline: writing

meeting logs & notes

7-8-16

Considering small groups and small teams / workgroup literature.

Next steps: Read through the previous papers on wikis that are English, and see what the general results and findings are. Then use our corpus to see how much of this holds across language editions, and how much of this seems to be more uniquely English oriented.

06-28-16

Thinking about ways to do small group analyses within the various language editions. Consider different approaches to network construction here. It would also be good to think about this with respect to things like sequential data analysis techniques like chain revision graphs, etc.

06-21-16

JM, DG, and AS discussed approach for communicating findings and for next steps. We might look into orgs, coordination, and collective intelligence lit.

05-22-16

DG: I spent some time looking at the data distributions and ran a bunch of models on the simple EN models overnight. The data for len_1 are reallllly long-tailed with very low frequencies -- this is causing the convergence issues. Below is a table of the simple model (len_1 ~ num_editors_1), run through a series of truncated data sets. The models will converge all the way up to removing the final data point out of the 4,077,819 data points we have. In other words, I was able to get convergence by dropping a single data point. Here's a quick table of the results from running the models:

RESOLVES	CUTOFF_LEN_1	PERCENT_DATA_COVERED	NUM_EDS1_COEFF	NUMEDS1_SE	ALPHA	FREQ_COUNTS_FOR_CUTOFF_BIN	NOTES
Yes	50	97.81%	0.1392615	0.0000551	0.05119	1,993
Yes	500	99.85%	0.1028963	0.0000536	0.2065	19
Yes	5000	99.99%	0.0913293	0.0000536	0.2743573	1
Yes	10000	99.99846%	0.0903963	0.0000536	0.2806345	1	missing only 63 data points (4077756/4077819)
Yes	50000	99.999975%	0.0896678	0.0000536	0.2858428	1	missing only 1 data point
No	no cutoff	100%	.	.	.	1	cannot compute an improvement, discontinuous region encountered

So, there are a few things we should take note of when looking at the data here:

len_1 ranges in this data set from: 2 - 133,529
as the cutoff increases (i.e., more data included in the model) the coeff for editors decreases (to be expected since we have longer tail) and the SE stabilizes around .0000536.
alpha also increases (as expected)
the last data point is len_1 = 133,529; but if you look at the tabs you get to 99.99% of the data at len_1 ~= 2500, and the last 5 len_1's are 28364, 30313, 34390, 44586, and then 133529. that's likely causing all kinds of havoc with numerous things (e.g., dispersion calculations, covariance and corr issues, etc.)

05-16-16

Jim, Darren, and Aaron discussed the introduction, related work, and research contribution for the CSCW paper. Related work: get away from lit review style of writing (for instance "we know that temporal issues are important (cite)", don't use authors as subjects, end each section for warent for our work; Discussion/Contribution: make a bulleted list of potential contributions for the paper.

05-11-16

Darren and Jim discussed the background section of the paper.

05-10-16

Aaron and Jim discussed the background section of the paper. Key takeaways: write the Durkhiem section more concisely and explicitly show the connection to our study, change the en:wp to be less lit-review-y and just show how it connects to ideas and expectations in the paper (also mention that it informs methods), cut a lot of "Applications to Organizations, Communities, and Social Movements", think of using Omnipedia earlier on because it shows that culture is acting as structuring (for content). Generally, think about building up conceptual relationships needed to understand the paper. Try writing a one sentence description of what each section is supposed to do in the paper.

05-04-16

Jim and Darren discussed a qualitative coding plan for the undergrads, and writing goals for the coming week. Jim showed Darren the location of data files on Jakku for future data analysis.

04-27-16

Jim and Darren discussed the overall outline of the paper and the framing of the background section. Specifically: 1) write the intro using the "the world is increasingly globalized" framing, 2) first include previous work on english wikipedia (especially on collaboration and bias, e.g. keegan, kittur, shaw, wagner, bryant), 3) then include small studies hyperlingual studies and studies on hyperlingual content (e.g. hecht, herring, hara), and 3) write about gap in previous lit (i.e. difference in collaboration practices)