Quantitative Analysis of User-Generated Content on the Web

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Information about Quantitative Analysis of User-Generated Content on the Web

Published on April 22, 2008

Author: xaoch

Source: slideshare.net

Description

Web Science Workshop at World Wide Web Conference 2008
Presentation that presents the results of measuring the user contribution to 9 UGC web-sites: Furl, Digg, Slideshare, FanFiction, Scribd, Revver, Merlot, Amazon Reviews and LibraryThing

Quantitative Analysis of User-Generated Content on the Web Xavier Ochoa, ESPOL, Ecuador Erik Duval, KULeuven, Bélgica

Topics Why? Studies Findings Implication of the Findings Conclusion FurterWork

Why?

Studies

Findings

Implication of the Findings

Conclusion

FurterWork

Why? UGC economy: Supply: Users publishing their content Demand: Users viewing content from others Currency: Attention

UGC economy:

Supply: Users publishing their content

Demand: Users viewing content from others

Currency: Attention

Why? Demand (Popularity) is relatively well understood: But Supply (Publication) is not.... How a ‘hit’ is born (S Sinha, RK Pan, 2006)

Demand (Popularity) is relatively well understood:

But Supply (Publication) is not....

Studies

Studies Descriptive Statistics Distribution Fitting Concentration Analysis

Descriptive Statistics

Distribution Fitting

Concentration Analysis

Findings Distribution of supply is not Normal

Distribution of supply is not Normal

Findings Distribution of supply has a heavy tail

Distribution of supply has a heavy tail

Findings Lotka (“fat-tail”) Weibull (“fat-belly”)

Implications of the Findings There is not such thing as an “average user ”

There is not such thing as an “average user ”

Low Class Middle Class High Class

Implications of the Findings The production of different UGC types is similar, but not the same.

The production of different UGC types is similar, but not the same.

Implications of the Findings Pareto Rule (80/20) applies to UGC (but no substitute to measuring)

Pareto Rule (80/20)

applies to UGC

(but no substitute to measuring)

Implications of the Findings “ Fat-tail” UGC production is similar to professional production.

“ Fat-tail” UGC production is similar to professional production.

Implications of Findings The distribution is not affected by site size or production effort

The distribution is not affected by site size

or production effort

Implications of the Findings Make your bet, head or tail?

Make your bet,

head or tail?

50% of Content is generated here

50% of Content is generated here

Implications of the Findings Informetrics can help us to understand UGC production (and vice versa)

Informetrics can help us to understand UGC production

(and vice versa)

Conclusions Measuring is our only way to test our hypothesis about how Web works If you admin a UGC-based site, measure production to gain insight on the other side of your economy Inequality of Contribution of UGC is real and should be dealt with in all its variations.

Measuring is our only way to test our hypothesis about how Web works

If you admin a UGC-based site, measure production to gain insight on the other side of your economy

Inequality of Contribution of UGC is real and should be dealt with in all its variations.

Further Work Modeling Production of UGC Integrate UGC inside the Informetrics / Scientometrics / Webometrics framework Expand the data collection and analysis Measure growth (size and contributors) Measure production rate Use at least 3 examples for each type of UGC

Modeling Production of UGC

Integrate UGC inside the Informetrics / Scientometrics / Webometrics framework

Expand the data collection and analysis

Measure growth (size and contributors)

Measure production rate

Use at least 3 examples for each type of UGC

Xie xie, questions? Xavier Ochoa – [email_address] Erik Duval – [email_address]

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