Difference between revisions of "Submissions:2018/Wikimedia Infrastructure for being nice"
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;[[Submissions#Academic Peer Review Option|Academic Peer Review option]]: yes |
;[[Submissions#Academic Peer Review Option|Academic Peer Review option]]: yes |
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;[[Submissions#Presentation Types|Type of submission]]: presentation |
;[[Submissions#Presentation Types|Type of submission]]: presentation |
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| − | ; |
+ | ;Authors: Lane Rasberry, Megan Wacha |
| − | ;E-mail address: {{Email|rasberry|virginia.edu}} |
+ | ;E-mail address: {{Email|rasberry|virginia.edu}}, {{Email|megan|wikimedianyc.org}} |
| − | ;Wikimedia username: [[user:bluerasberry]] |
+ | ;Wikimedia username: [[user:bluerasberry]], [https://en.wikipedia.org/wiki/User:Megs| User:Megs] |
| − | ;Affiliation(s) (optional): <!-- Organization, company, Wikimedia affiliate, etc. --> University of Virginia |
+ | ;Affiliation(s) (optional): <!-- Organization, company, Wikimedia affiliate, etc. --> University of Virginia, Wikimedia New York City |
;Abstract: <!-- At least 300 words to describe your proposal, can also link to any pages, slidedecks, etc. that you may have. --> |
;Abstract: <!-- At least 300 words to describe your proposal, can also link to any pages, slidedecks, etc. that you may have. --> |
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Presenter Lane Rasberry briefly describes some past research in Wikimedia civility. Following this, a researcher from the University of Virginia presents "[[:meta:University of Virginia/Machine learning to predict Wikimedia user blocks|Machine learning to predict Wikimedia user blocks]]" an ongoing research project by graduate student researchers from the Data Science Institute at the University of Virginia. In this project students seek to use machine learning to automate the detection of civility problems to flag for further human review. |
Presenter Lane Rasberry briefly describes some past research in Wikimedia civility. Following this, a researcher from the University of Virginia presents "[[:meta:University of Virginia/Machine learning to predict Wikimedia user blocks|Machine learning to predict Wikimedia user blocks]]" an ongoing research project by graduate student researchers from the Data Science Institute at the University of Virginia. In this project students seek to use machine learning to automate the detection of civility problems to flag for further human review. |
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| − | ;Length of presentation: <!-- 30-45 min. for panels, 30-75 min. for workshops, 15-30 min. for presentations --> |
+ | ;Length of presentation: <!-- 30-45 min. for panels, 30-75 min. for workshops, 15-30 min. for presentations --> 30 minutes |
;Special requests: <!-- For example - technology requirements, can not present at specific times, etc. --> slides |
;Special requests: <!-- For example - technology requirements, can not present at specific times, etc. --> slides |
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Revision as of 20:07, 15 August 2018
This submission has been noted and is pending review for WikiConference North America 2018.
- Title
- Theme (optional)
- Harassment, Civility, & Safety
- Academic Peer Review option
- yes
- Type of submission
- presentation
- Authors
- Lane Rasberry, Megan Wacha
- E-mail address
- rasberry
virginia.edu, meganwikimedianyc.org
- Wikimedia username
- user:bluerasberry, User:Megs
- Affiliation(s) (optional)
- University of Virginia, Wikimedia New York City
- Abstract
Anyone may join for a beginner's introduction to the infrastructure of civility in Wikimedia projects. The focus will be on the workflow of keeping safe spaces in Wikimedia's online and in-person spaces. While individuals personally handle some tasks, many aspects of Wikimedia friendly space are a result of infrastructure built into the design of the Wikimedia user experience.
Presenter Lane Rasberry briefly describes some past research in Wikimedia civility. Following this, a researcher from the University of Virginia presents "Machine learning to predict Wikimedia user blocks" an ongoing research project by graduate student researchers from the Data Science Institute at the University of Virginia. In this project students seek to use machine learning to automate the detection of civility problems to flag for further human review.
- Length of presentation
- 30 minutes
- Special requests
- slides
- Preferred room size
- 25
- Have you presented on this topic previously? If yes, where/when?
- no
- If you will be incorporating a slidedeck during your presentation, do you agree to upload it to Commons before your session, with a CC-BY-SA 4.0 license, including suitable attribution in the slidedeck for any images used?
- yes
- Will you attend WikiConference North America if your submission is not accepted?
- yes
Interested attendees
If you are interested in attending this session, please sign with your username below. This will help reviewers to decide which sessions are of high interest. Sign with four tildes. (~~~~).