Download - When visibility means power
![Page 1: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/1.jpg)
When visibility means power Tracking political races from the Internet
Stephane Gauvin Université Laval ECIG: October 2009
![Page 2: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/2.jpg)
![Page 3: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/3.jpg)
![Page 4: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/4.jpg)
![Page 5: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/5.jpg)
![Page 6: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/6.jpg)
What can we learn from
Search engines count data?
Webometrics The 2004 experience The 2009 experience (USA) The 2009 experience (Canada) Building a measurement scale Meaning and sentimentalism
![Page 7: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/7.jpg)
Webometrics – painful beginnings
1996: WordOfNet measures visibility Closely aligned with SEO Highly unreliable – disappears 2001
2003: Factiva’s visibility index Venture owned by Dow Jones & Reuters Tracks media mentions of democrats
![Page 8: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/8.jpg)
2004 Democrat convention
![Page 9: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/9.jpg)
2004 consensus
Web based metrics unreliable See:
Bar-Ilan, 2001, 2008 Björneborn & Ingwersen, 2001 Clarke & Willett, 1997 Cothey, 2004 Ingwersen & Björneborn, 2005 Lawrence & Giles, 1999 Mettrop & Nieuwenhuysen, 2001 Oppenheim, Morris, McKnight, & Lowley, 2000 Shafi & Rather, 2005 Snyder & Rosenbaum, 1999 Vaughan & Thelwall, 2004
That was before the social www 2004: 1M blogs / 2009 200M blogs 2004: 4G urls / 2009 1T urls
![Page 10: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/10.jpg)
Measurement issues Latency
Unlike stars in the sky, visibility doesn’t reveal itself Document centric (url seed(s) and follow links)
• Amounts to convenience sampling • Bias is shown in Vaughan & Thelwall 2004
Concept centric (rely on extensive generic crawling/indexing – i.e. Google)
Domain definition Narrow (Senator John McCain) Wide (McCain) Variants (typos, nicknames)
Variance Ex: Yahoo! doesn’t agree with Google (next slide)
Partitions Digital space is not homogeneous: news, blogs, social, images, videos, www
![Page 11: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/11.jpg)
Raw scores all over the place
![Page 12: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/12.jpg)
Building a measurement scale
Identify independent instruments
Harvest data
Weed out using Cronbach’s alpha
![Page 13: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/13.jpg)
Independent instruments
![Page 14: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/14.jpg)
Harvest data Every day, a script mimics a user (not an API using a
sub-index)
Up to 6 trials if the engine fails to return a result (dropped connexion, busy, etc.)
Machine parsed to extract count data
Compute visibility shares to alleviate extreme outliers (engines may return results several orders of magnitude larger than what they should be, which makes correlations unreliable. Visibility shares are always in to 0..1 interval)
![Page 15: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/15.jpg)
High reliability
Google often low
![Page 16: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/16.jpg)
2009 US presidential
![Page 17: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/17.jpg)
2008 : Harper vs Dion
![Page 18: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/18.jpg)
Blogs as early signal?
![Page 19: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/19.jpg)
Blogs as early signal?
![Page 20: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/20.jpg)
Visibility vs opinion polls
![Page 21: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/21.jpg)
Correlations between signals
Absolute values above .18 are significant at p < 0.05
![Page 22: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/22.jpg)
Summary
Web metrics are highly reliable They appear to be valid indicators
French presidential US presidential Canadian elections
But Anecdotal (only 2-3 instances) In the political realm (what about brands or social themes?) Questionable (what about sentiment?)
![Page 23: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/23.jpg)
Sentiment
Mere visibility works because it embodies sentiment i.e. a rotten politician will soon become « invisible »
Changes in visibility may convey sentiment (steady gains signals positive, explosion signals negative)
Sentiment analysis is difficult for several reasons: Volume makes human analysis impractical Complexity makes machine analysis difficult Conceptually not clear what is good or bad (pro-life?)
![Page 24: When visibility means power](https://reader034.vdocument.in/reader034/viewer/2022051323/547c964db379595e2b8b5020/html5/thumbnails/24.jpg)
Next
Apply to other concepts Investigate metric properties
Consider simple sentiment analysis (SA) Goal is to call turning points (ex: Gore gets Nobel,
Spitzer gets prostitute) When there is a news storm, sentiment is usually
obvious, making SA pointless But some events are ambiguous (ex: Sarkozy-Bruni) And other events are unsentimental (ex: H1N1)