Notes

Controversy Indicators

Indicators

1. inside or outside forum,
2. past or present,
3. quantity,
4. nr. of different actors,
5. type of actors (established or not),
6. alignment,
7. type of spheres,
8. direction between spheres
9. maturity,
10. keywords in context
11. insiders posing as outsiders and visa versa (whistle blowers versus expert layman)
12. Leaders and followers

Previous indicators; association by link (whom links to whom):

1. kinds of links
2. pagerank actor for the issue
3. level of issue specificity (actor versus issue network). (Googlescraper app which associates actors with issues)

Previous indicators; barometer:

1. temperature/heath: hot / cold (freshness of pages)
2. debate activity/position taking: intense / mild (% of actors with position)
3. de-territorialization: many countries / one country (% of max country involvement)

KWIC (Keywords in Context) / Controversy-typical keywords

• real, junk, fact vs fiction, myth, hysteria, hype, controversy, risk, danger, death, opponent, proponent, concerns, stakeholders, advocates, ngo, lobbying, pro / con, whistle blowing, leak, for /against dispute, policy
• Mood: disagreement, uncertainty, doubt, leak, so-called

Thoughts

• Latour: Controversy itself is controversial. use of the word in order to re-open debates
• To which actors are controversies relevant?
• Astroturf / Lipmann
• Level of professionalization of (actors in) controversy + jobtitles + professionals acting as publics

Related stuff

Affect Browser

Christian Nold
2006 - ongoing

The Affect Browser is a tool for extracting and visualising the hidden emotional slant of any text (English for now). In particular it tries to show how an individual text relates semantically to a group of others that are focused on a particular topic.

The software uses a dictonary of positive and negative affect (emotion) words such as "lovely, great,terrible" to draw a series of word clouds. Red is positive, blue negative while the yellow cloud shows the 10 most frequently used words for the text with stop words like "the, and , it" removed.
The resulting diagram is both a content summary as well as an indication of its emotional slanting.

http://www.softhook.com/affect.htm

We Feel Fine

http://www.wefeelfine.com

Our delicious bookmarks

http://del.icio.us/tag/dmi_uva

Useful

http://www.opencalais.com/about

Réseau LU

Media Analysis with Reseau Lu

Presentation by Andrei Mogoutov

Media Analysis with ReseauLu includes news, blogs, publications in traditional media

Method
1. define discourse frames
frames should be frames that are locatable in those frames
considerations
- treating spheres symmetrically terms should be likely to appear in all spheres
- when treating science symmetrically with news pick terms occurring across spheres

2. search in database (factiva or lexus nexus )
factiva: newspapers and business news
interesting indexation
keywords, abstract, companies, actors, lot of data

or:
2. Google Web Search

or:
2. Scientific (Web of Science)

or
2. search in blogs
Google blog search
sort by date
save rss
queries derived from map analysis
"green home" + water
"green home" + plastic

3. open reseaulu
create project & name
import the data
compare domain and file in reseaulu
good way to come to starting points for further exploration

4. maybe check out the other data, for instance take the teaser texts
run script textual analysis
export and clean up the data in /xls
data care in column with theme
delete old file and import new
semantic analysis script
map with ReseauLU
good way to come up with extended keywords list and analyze the co-occurence of the themes that were extracted from teaser texts

-- EstherWeltevrede - 18 Jul 2008