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how to measure participation rates
by Katerina 05 Dec '03

05 Dec '03

Thank you all for your valuable help. Nescan seems to be a tool applicable to newsgroups and not web-based discussion forums. I have contacted a PERL programmer and I am waiting for a reply. If this doesn't work I will have to carry it through manually. I am thinking that I could use a sample of the messages, for example the two most popular conferences, and analyse their messages instead of attempting the impossible task of analyzing the total of the interactions in the group. Thank you once more, K.D.

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fAf: 2004 Media Arts & Screen Calendar Now Online
by linda carroli 04 Dec '03

04 Dec '03

fineArt forum Special Notice: 2004 Media Arts & Screen Events & Deadlines Calendar Now Online After scanning recent back issues, fineArt forum presents its 2004 Events & Deadlines Calendar. Until fAf returns from a break in production, it is hoped that the Calendar will provide a quick and easy reference for information about events and calls in 2004. The Calendar is a selected compilation of new media arts postings sifted from fAf back issues, various lists and email inbox. It is by no means comprehensive and is not generated from a database. The Calendar is an attempt to keep information simple, chronological, current and relevant without the pressure of publishing a monthly magazine. fAf will endeavour to update it from time to time and hope it is a useful resource until fAf's return in the first quarter of next year. 2004 Events & Deadlines Calendar http://www.fineartforum.org/Backissues/Vol_18/calendar_index.html fineArt forum art + technology netnews http://www.fineartforum.org editor(a)fineartforum.org

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response on ginis
by Philip Howard 04 Dec '03

04 Dec '03

Max Forte is absolutely right that using gini coefficients this way would require that the researcher make sensible judgments about attribution and content value. To really know your subjects and their relationship a researcher probably would need deep experience with their interactions. However, the graph could be composed even if the researcher had no qualitative experience with the group, using number of people on one axis and number of words, number of lines, number of sentences, number of posts (as Hendricksen does). These things easy to count no need for qualitative judgments. Probably more interesting would be to graph number of people on one axis and good ideas generated, smart repartee or meaningful engagement on the other axis. These things would require deep knowledge of the group and a qualitative researchers instinct for how to define, measure and attribute a good contribution. A qualitative researchers insight would also be needed to figure out any causal connection there might be between being a member of a social elite, writing a lot of text, and generating good ideas. The coding would probably have to be done by hand. I interpreted the original post to be a query about how to measure any deviance from a perfectly egalitarian group, where all the respondents participate equally, generating the same amount of text, ideas, or hot air. Mathematically we can know what that perfect distribution is, so my gini idea is just a way of calculating deviation from that ideal. I absolutely would not argue that ginis can be meaningful alone, for the reasons Forte offers. I like the qualitative approach that then provides some quantitative context to show how qualitative findings are transportable. And anyway multi method triangulation is always best. I originally suggested that the number would be most useful in a comparative context. Lakhani agrees, and even if we did ginis for AIR it would be interesting to compare ginis on different topics or variation over time. He also points out that there would be noise inany database of content, but there must be a way of doing somekind of confidence interval, error term on the datapoints, or significance tests on the gini itself. My math skills end here, so if anyone can develop a significance test for a quantitative measure of deviation from a theoretically perfect distribution of content/ideas in a group of people please post it! But please dont do it to the AIR list too inside baseball I think. p. Philip N. Howard Assistant Professor Department of Communication University of Washington http://faculty.washington.edu/pnhoward/

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gini coefficients for measuring participation?
by Philip Howard 04 Dec '03

04 Dec '03

One possibility that would not involve writing a program, would be to calculate the distribution of messages in the same way that economists calculate the distribution of wealth in a country. They create an index of population (0% of the people to 100% of the people) and an index of the wealth (0% of the wealth to 100% of the wealth). In a perfectly egalitarian country 10% of the people have 10% of the wealth, 50% of the people have 50% of the wealth, etc, and you can graph the slope 1=1. In an inegalitarian country 10% of the people have 40% of the wealth, 50% of the people have 80% of the wealth and when you graph all of the points you get a curve of inequality. There is a basic calculus method for calculating the area of the graph between the perfectly egalitarian distribution (1=1 slope) and the ineglitarian distribution (wierd slope), and this is called the gini coefficient. Scandinavian countries ahve a small gini coefficient and Brazil has a big gini coefficient. So you might take a sample day or week, count the messages, and then label each message by the author's name. Say you have 1000 messages but only 100 authors. Graph this, 10% of the authors write XX% of the messages, 20% of the authors write XXX% of the messages, and so on up to 100% of the authors writing 100% of the messages. The area of the graph between the egalitarian distribution of messages and your sample gives you a measure of content inequality - how much of the content is generated by an elite group. If the metric is low your group is pretty egalitarian, if the metric is high you have a clique generating most of the content. The metric would be most meaningful if you could compare it to another group's metric, so if you did this over several sample periods, you could say whether the distribution of message posts was getting more or less egalitarian / elitist as the list was evolving. would make purdy graphs, and could be used for almost any sample of content & authors where you can attribute 100% of the content to 100% of the authors. p. Philip N. Howard Assistant Professor Department of Communication University of Washington http://faculty.washington.edu/pnhoward/

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RE: [Air-l] Late adolescents and dating on the Internet
by Frank Thomas 04 Dec '03

04 Dec '03

There is an article on the website of the New York Times today that shows the limits of the business: human feelings, saturation. It might help to situate your issue. And specially, what a term: increasing dating fatigue! Just Saying No to the Dating Industry December 2, 2003 By KATE ZERNIKE BY her own admission, Sara Cambridge was "totally cruising." She spent hours trolling online dating sites, sending e-mail messages to potential mates and creating "a real connection," which would invariably sour into deep disappointment within the first five minutes of an actual date. At which point she would return to the sites, send more e-mail, make another connection and suffer another snap disappointment. ... http://www.nytimes.com/2003/12/02/fashion/30SING.html?ex=1071533063&ei=1&en… Copyright 2003 The New York Times Company -- ...................... Dr. Frank Thomas FTR Internet Research Rosny, France

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post-docs
by Katerina 04 Dec '03

04 Dec '03

For those interested in post-doctoral opportunities, this is the only web site I found: http://www.postdocjobs.com K. Diamantaki

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RE: [Air-l] Late adolescents and dating on the Internet
by cecilie mortensen 04 Dec '03

04 Dec '03

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computer games and uzbekistan
by david silver 04 Dec '03

04 Dec '03

Uzbekistan and computer games, via the BBC and beth kolko: http://news.bbc.co.uk/1/hi/technology/3246092.stm david

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Grad Seat Monthly Report
by Nancy Baym 03 Dec '03

03 Dec '03

Here is the monthly report from the graduate representative Leslie Tkach Kawasaki. My email has been flaky this week, so I apologize to Leslie for not including it in the monthly report: This past month, in addition to giving opinions at times on various AoIR executive matters, I have mainly been (a) discussing AoIR with colleagues here and strategies for promoting AoIR here in Japan (translations are necessary!); and (b) considering potential activities for graduate students in Sussex next year. -- Nancy Baym http://www.ku.edu/home/nbaym Communication Studies, University of Kansas Bailey Hall, 1440 Jayhawk Blvd., Room 102, Lawrence, KS 66045-7574, USA Association of Internet Researchers: http://aoir.org

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RE: [Air-l] how to measure participation rates
by Kylie Veale 03 Dec '03

03 Dec '03

Katerina, If youre looking at USENET newsgroups, you might want to take a look at the social accounting search engine NetScan at http://netscan.research.microsoft.com. I successfully used the muscle of their automated newsgroup participation statistics for a recent study I performed; Discussing Our Family Trees: Finding Community-Based Communication in Genealogical Newsgroups. I used the Common Ground Model of Whittaker, Terveen, Hill, and Cherny (1998), and the Online Community (OC) Model of Scoberth, Preece, and Heinzl (2003), to test for online community the NetScan database statistics worked fabulously well (though I did also use some manually collated stats for some specific OC tests). I studied four years of data for the newsgroup in my study, which had over 123,000 posts during that period. Regards Kylie Veale | Brisbane, Australia GradDipInvEnv, MInetStds [2003] email: kylie(a)veale.com.au www: http://casa.de.veale.com.au www: http://www.veale.com.au/kylie -----Original Message----- From: air-l-admin(a)aoir.org [mailto:air-l-admin@aoir.org] On Behalf Of Katerina Sent: Wednesday, 3 December 2003 1:42 AM To: air-l(a)aoir.org Subject: [Air-l] how to measure participation rates As part of my study of an online community I have to measure the participation rates among participants, in a way similar to Nancy Baym's in her classic study of the r.a.t.s online community. From my participation and observation of this particular community so far, it is obvious to me that most of the messages are contributed by a small group of heavy users. However, I need to quantify it, measure it and present it as a table containing percentages of posters and posts contributed. My question is how can I do it? What is the method of measuring these rates? Does it simply consist in noting down how many messages each member writes? Prima facie that may look like an easy procedure but once starting to do it it turns out to be extremely difficult since this online community is made up of more than 20 conferences each one comprising more than 50 different topical discussions. Overall the number of messages written every week is enormous. Any ideas on how I can measure overall participatio rates of such an environment? Thank you, K. Diamantaki

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