User:OrenBochman/WGT/Research Questions
Research Question 1 - Population Dynamics edit
General population dynamics questions are:
- How many members are there in the community of wiki X?
- What is the size of the active community?
- How many members occupy different social roles.
- How long do members occupy different social roles. (Life span)
- What is the population over time on different wikis?
- How do these relate to changes in the overall population of the wiki?
- How do these relate to readership of the wiki over time?
- How do these relate to existence of robot members of the population.
- what number of players in different social roles are required to sustain different wikis. (e.g. against incoming spam)
- how do wikis cope with catastrophic and non-catastrophic decline in population size and funding. (e.g. 9/11 wiki).
- relate changing population dynamics to openness of the wiki and its policy complexity.
WGT population dynamics are:
- What is the incidence of a specific game
- At each play what strategy was employed by each player
- What was the outcome.
- What is the ESS.
- How do theoretical payoffs correlate with outcome payoff in one shot and many shot games given cost and benefits?
To answer so many interrelated questions - it will be necessary to :
- gather information on these numbers.
- API based checkers running periodically on many wikis.
- dump based script that get this using SNA.
- produce a population models.
To support quantitative investigation especially dynamically modeling of stability and fragility it is necessary to use real world numbers.
Note: sampling this information should be automated and run daily.
DATE: XX/XX/XXXX
| Group | API Count | > 1/4*7 day mean activity count | > 1/4*30 days activity count | > 1/4*90 day activity count | |
|---|---|---|---|---|---|
| admins on Wikipedia | 1500 | 370 | |||
| autopatrollers | 2677 | ||||
| rollbackers | 2677 | ||||
| registered | 2677 | ||||
| anonymous | |||||
| bots |
| Group | Count | 7 day SD | Source |
|---|---|---|---|
| total articles | |||
| creation daily | |||
| CSD daily | 100 | ||
| AdD daily | 100 | ||
| WP:Prod daily | 100 | ||
| afd currently open | 700 | 350 |
| Group | Count | inc | dec | deletion delta |
|---|---|---|---|---|
| Articles | +20 | +200 | -180 | 0 |
| Talk | +20 | +200 | -180 | 0 |
| Talk - h-index | +20 | +200 | -180 | 0 |
| Article + Talk hindex | +20 | +200 | -180 | 0 |
| Tagging Art | +100 | +200 | -300 | 100 |
| Tagging inline | 40 | -40 | 20 | |
| Cat | 330 | 350 | -20 | 0 |
| Policy Ref | 100 | 100 | 0 | 0 |
| Policy Mass | 100 | 120 | -20 | 0 |
Bases on SNA we can also look at "Social events"
| Group | Count | %anon | %bot | %admin | %role X |
|---|---|---|---|---|---|
| Edit War | 20 | 40 | 20 | 30 | 0 |
| WikiQuette | 600 | 80 | 15 | 1 | 4 |
| Biting | 40 | 50 | 45 | 1 | 4 |
| Consensus Success | 700 | 5 | 45 | 25 | 95 |
| Consensus Failure | 100 | 5 | 0 | 5 | 95 |
TO update these on a regular basis I will have to extend the following script User:OrenBochman/Rbot/Variables.py and expand it to to work with SNA packages.
Research Question 2 - Social Learning Curve edit
- What are the rules of the game?
- How many rules of policy must be mastered by players ?
- How has WP name space growing compared with Mainspace ?
- How many help pages are the
| Group | Count | 7 day SD | Source |
|---|---|---|---|
| total WP: pages | |||
| Policy pages | 100 | ||
| Guideline pages | 700 | 350 | |
| Essays | 700 | 350 |
is policy growing relatively faster than article space? [1]
Research Question 3 - Cost to Benefit Estimation edit
Game have cost and benefits associated with them. Writing articles in particular has costs associated with them. Costs can be discount using technology. UI support (Google scholar Mashup) or ProveIt UI.
Research Question 3.1 - Cost of Editing edit
Editing Costs:
- Time
- Information added
- Information complexity (citation).
- Information complexity discount (e.g. using proveIt to cite).
- Editing Complexity (templates).
- etc
Editing benefits:
- Fun factor
- Advancement - recognition, barn stars.
- The gift: Mutual information gain.
- Leaning.
- Altruism:
- Memematic Kin altruism [We are closely related Memematicaly]
- Memematic Group altruism [We are closely related Memematicaly as a group]
- Direct reciprocity effect.
- Indirect reciprocity effect.
- Network reciprocity effect.
- etc.
The question boils down to:
- In a given social situation how can we quantify cost to benefit ratios based on overall player interaction??
Research Question 3.2 - Cost of Communication edit
Extending the question above to Communication scenarios, both simple games and looking at conversations and at repeated conversations.
Research Question 3.3 - Cost of Coordination edit
- How many centralized coordination spaces are there
- Article Page
- AfD...MfD
- etc
- ↑ F. B. Viegas, M. Wattenberg, J. Kriss, and F. van Ham. (2007). "Talk before you type: Coordination in Wikipedia." (PDF). HICSS: 78–78.