Hi everyone,
We’re preparing for the January 2020 research newsletter and looking for contributors. Please take a look at https://etherpad.wikimedia.org/p/WRN202001 and add your name next to any paper you are interested in covering. Our writing deadline is 25 January 23:59 UTC. If you can't make this deadline but would like to cover a particular paper in the subsequent issue, leave a note next to the paper's entry below. As usual, short notes and one-paragraph reviews are most welcome.
Highlights from this month:
- ‘WP2Cochrane’, a tool linking Wikipedia to the Cochrane Library: Results of a bibliometric analysis evaluating article quality and importance
- Building Knowledge Graphs: Processing Infrastructure and Named Entity Linking
- Individual and collaborative information behaviour of Wikipedians in the context of their involvement with Hebrew Wikipedia
- Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems
- Knowledge curation work in Wikidata WikiProject discussions
- Knowledge curation work in Wikidata WikiProject discussions
- Strangers in a seemingly open-to-all website: the gender bias in Wikipedia
- Understanding Wikipedia as a Resource for Opportunistic Learning of Computing Concepts
Masssly and Tilman Bayer
[1] http://meta.wikimedia.org/wiki/Research:Newsletter[2] WikiResearch (@WikiResearch) | Twitter
Hey Research Community,
TL;DR New dataset:
https://figshare.com/articles/Wikipedia_Articles_and_Associated_WikiProject…
More details:
I wanted to notify everyone that we have published a dataset of the
articles on English Wikipedia that have been tagged by WikiProjects [1]
through templates on their associated talk pages. We are not planning to
make this an ongoing release, but I have provided the script that I used to
generate it in the Figshare item so that others might update / adjust to
meet their needs.
As anyone who has done research on WikiProjects knows, it can be
complicated to determine what articles fit under a particular WikiProject's
purview. The motivation for generating this dataset was to support our work
in developing topic models for Wikipedia (see [2] for an overview), but we
imagine that there are many other ways in which this dataset might be
useful:
* Previous work has examined how active WikiProjects are based on edits to
their pages in the Wikipedia namespace. This dataset makes it much easier
to identify which Wikiprojects are managing the most valuable articles on
Wikipedia (in terms of quality or pageviews).
* Many topic-level analyses of Wikipedia rely on the category network.
Categories can be very messy and difficult to work with, but WikiProjects
represent an alternative that often is simpler and still quite rich. For
instance, this could be used for temporal analyses of article quality,
demand, or distribution by topic.
* While WikiProjects are English-only and therefore limited in their
utility to other languages, we also provide the Wikidata ID and sitelinks
-- i.e. titles for corresponding articles in other languages -- to allow
for multilingual analyses. This could be used to compare gaps in coverage
-- e.g., akin to past work that has used categories [3].
The main challenge, besides processing time, is how to 1) effectively
extract the WikiProject templates from talk pages, and, 2) consistently
link them to a canonical WikiProject name and topic. For example, the
canonical template for WikiProject Medicine is
https://en.wikipedia.org/wiki/Template:WikiProject_Medicine but another one
used is
https://en.wikipedia.org/w/index.php?title=Template:WPMED&redirect=no (and
there are 13 more). To capture articles tagged with these many templates
and all link them to the same canonical WikiProject and eventually
higher-level topic, we built a near-complete list of WikiProjects based on
the WikiProject Directory [4] and gathered all of their associated
templates. We purposefully excluded WikiProjects under the assistance /
maintenance category [5]. When parsing talk pages from the dump files then,
we check for any of these templates and list them under their canonical
name. As a backup, we also employ case-insensitive string matching with
"WP" and "WikiProject", which helps to guarantee that we did not miss any
WikiProjects but introduces a number of false positives as well. If you
wish to map the WikiProjects listed in the dataset to their higher-level
topics, the mapping is in the figshare item and code that allows you to do
that can be found here:
https://github.com/wikimedia/drafttopic/blob/master/drafttopic/utilities/ta…
[1] https://en.wikipedia.org/wiki/Wikipedia:WikiProject_Council
[2] https://dl.acm.org/doi/10.1145/3274290
[3]
https://meta.wikimedia.org/wiki/Research:Newsletter/2019/September#Wikipedi…
[4] https://en.wikipedia.org/wiki/Wikipedia:WikiProject_Council/Directory
[5]
https://en.wikipedia.org/wiki/Wikipedia:WikiProject_Council/Directory/Wikip…
Best,
Isaac
--
Isaac Johnson (he/him/his) -- Research Scientist -- Wikimedia Foundation
That's fascinating, John; thank you. I'm copying this to wiki-research-l and
Fabian Suchanek, who gave the first part of the Research Showcase last month.
What do you like for coding stories? https://quanteda.io/reference/dfm.html ?
Sentiment is hard because errors are often 180 degrees away from correct.
How do you both feel about Soru et al (June 2018) "Neural Machine Translation
for Query Construction and Composition"
https://www.researchgate.net/publication/326030040 ?
On Sat, Jan 11, 2020 at 3:46 PM John Urbanik <johnurbanik(a)gmail.com> wrote:
>
> Jim,
>
> I used to work as the chief data scientist at Collin's company.
>
> I'd suggest looking at things like relationships between the views / edits for sets of pages as well as aggregating large sets of page views for different pages in various ways. There isn't a lot of literature that is directly applicable, and I can't disclose the precise methods being used due to NDA.
>
> In general, much of the pageview data is weibull or GEV distributed on top of being non-stationary, so I'd suggest looking into papers from extreme value theory literature as well as literature around Hawkes/Queue-Hawkes processes. Most traditional ML and signal processing is not very effective without doing some pretty substantial pre-processing, and even then things are pretty messy, depending on what you're trying to predict; most variables are heteroskedastic w.r.t pageviews and there are a lot of real world events that can cause false positives.
>
> Further, concept drift is pretty rapid in this space and structural breaks happen quite frequently, so the reliability of a given predictor can change extremely rapidly. Understanding how much training data to use for a given prediction problem is itself a super interesting problem since there may be some horizon after which the predictor loses power, but decreasing the horizon too much means over fitting and loss of statistical significance.
>
> Good luck!
>
> John
Hello,
to everyone to whom it concerns, my best wishes for the year 2020!
I am interested in the number of scientific papers or monographies,
articles etc. about wikis. Do you know about a paper that has come up with
a relatively recent number?
In my understanding, there are several problems that make it unwise to
simply search for "wiki" in a general catalogue:
* the word wiki can appear in words such as "Wikinger" (German for:
viking), or it is used as a metaphor (e.g., for a reform of democracy)
* some entities such as Wikileaks have "wiki" in their name, but are no
wikis, and some entities such as Open Street Map are wikis, but don't have
the word in their name
* wiki relevant topics may appear under terms such as "collaborative
writing" or "open content creation".
Kind regards
Ziko
The December 2019 issue of the Wikimedia Research Newsletter is out:
https://meta.wikimedia.org/wiki/Research:Newsletter/2019/December
In this issue:
1 Using Wikipedia to promote acoustics knowledge for the International Year of Sound 2020
2 Wiki Workshop 2019
2.1 Thanks" feature has "strong positive effect on short-term editor activity
2.2 What’s in the Content of Wikipedia’s Article for Deletion Discussions? Towards a Visual Analytic Approach
2.3 An awareness campaign in India did not affect Wikipedia pageviews, but a new software feature did
2.4 How Partisanship and Perceived Political Bias Affect Wikipedia Entries of News Sources
2.5 A Graph-Structured Dataset for Wikipedia Research
2.6 Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata
2.7 Inferring Advertiser Sentiment in Online Articles using Wikipedia Footnotes
2.8 Learning to Map Wikidata Entities To Predefined Topics
2.9 English Wikipedia's medical articles are of higher quality than those of Portuguese Wikipedia
2.10 Understanding Travel from Web Queries Using Domain Knowledge from Wikipedia"
2.11 Open Personalized Navigation on the Sandbox of Wiki Pages
3 Briefly
4 Other recent publications
4.1 In its war coverage, "Wikipedia shows greater conciliatory potential" than museums
4.2 The Global Popularity of William Shakespeare in 303 Wikipedias
4.3 Mapping the backbone of the Humanities through the eyes of Wikipedia
*** 15 recent publications were covered or listed in this issue ***
Masssly and Tilman Bayer
---
Wikimedia Research Newsletter
https://meta.wikimedia.org/wiki/Research:Newsletter/
* Follow us on Twitter: @WikiResearch
* Like us on Facebook: Facebook.com/WikiResearch/
* Receive this newsletter by mail: Research-newsletter Mailing List - Wikimedia
Apologies for cross-posting
====
SEMANTiCS - 16th International Conference on Semantic Systems, September
7 - 10, 2020
Amsterdam, The Netherlands
https://2020-eu.semantics.cc/
====
= Important Dates (specific track dates are given below)
* Abstract Submission Deadline: April 18, 2020 (11:59 pm, Hawaiitime)
* Paper Submission Deadline: April 25, 2020
(11:59pm,Hawaii time)
* Notification of Acceptance: June 08, 2020 (11:59
pm,Hawaii time)
* Camera-Ready Paper: July 06, 2020
(11:59pm, Hawaii time)
= Read a detailed description of all available calls online:
https://2020-eu.semantics.cc/calls
= Submission via Easychair on
https://easychair.org/my/conference?conf=sem20eu#
Proceedings of SEMANTiCS 2020 EU are planned to be published by Springer
LNCS & CEUR. All proceedings will be made available open access.
SEMANTiCS 2020 EU particularly welcomes submissions on the following key
topics:
* Web Semantics & Linked (Open) Data
* Enterprise Knowledge Graphs, Graph Data Management and Deep Semantics
* Machine Learning & Deep Learning Techniques
* Semantic Information Management & Knowledge Integration
* Terminology, Thesaurus & Ontology Management
* Data Mining and Knowledge Discovery
* Reasoning, Rules and Policies
* Natural Language Processing
* Data Quality Management and Assurance
* Explainable Artificial Intelligence
* Semantics in Data Science
* Trust, Data Privacy, and Security with Semantic Technologies
* Economics of Data, Data Services and Data Ecosystems
-------
* Special Sub-Topic: Digital Humanities and Cultural Heritage
* Special Sub-Topic: LegalTech
* Special Sub-Topic: Blockchain and Semantics
We especially encourage contributions that illustrate the applicability
of the topics mentioned above for industrial purposes and/or illustrate
the business relevance of their contribution for specific industries.
We invite contributions to the following tracks:
= Read a detailed description of all available calls online:
https://2020-eu.semantics.cc/calls
== Research and Innovation Track ==
The Research and Innovation track at SEMANTiCS welcomes papers on novel
scientific research and/or innovations relevant to the topics of the
conference. Submissions must be original and must not have been
submitted for publication elsewhere. Papers must follow the guidelines
given in the author instructions, including references and optional
appendices. Each submission will be reviewed by several PC members who
will judge it based on its innovativeness, appropriateness, and impact
of results in terms of effectiveness at solving real problems.
= Important Dates:
* Abstract Submission Deadline: April 18, 2020 (11:59 pm, Hawaii
time)
* Paper Submission Deadline: April 25, 2020 (11:59 pm,
Hawaii time)
* Notification of Acceptance: June 08, 2020 (11:59 pm,
Hawaii time)
* Camera-Ready Paper: July 06, 2020 (11:59
pm, Hawaii time)
Author instructions: Reviews will be carried out in a single-blind mode.
Long papers should have a maximum length of 15 pages and short papers of
6 pages. Submissions should follow the guidelines of the Springer LNCS
format. The detailed Call for Research and Innovation papers is
available here: https://2020-eu.semantics.cc/calls
== Posters and Demos Track ==
The Posters and Demonstrations Track invites innovative work in
progress, late-breaking research and innovation results, and smaller
contributions in all fields related to the Semantic Web and Linked Data
in a broader sense. These include submissions on innovative applications
with impact on end users, such as demos of solutions that users may test
or that are yet in the conceptual phase but are worth discussing, and
also applications or pieces of code that may attract developers and
potential research or business partners.
= Important Dates:
* Paper Submission Deadline: June 22, 2020 (11:59 pm,
Hawaii time)
* Notification of Acceptance: July 22, 2020 (11:59 pm,
Hawaii time)
* Camera-Ready Paper: August 01, 2020 (11:59
pm, Hawaii time)
Author instructions: Proceedings are planned to be published via CEUR
Workshop Proceedings and should follow the guidelines of the Springer
LNCS format. The detailed Call for Poster and Demos papers is available
online.
== Industry and Use Case Track ==
Focusing strongly on industry needs and ground breaking technology
trends SEMANTICS invites presentations on enterprise solutions that deal
with semantic processing of data and/or information. A special focus of
Semantics 2019 will be on the convergence of machine learning techniques
and knowledge graphs. Additional topics of interest are Enterprise
Knowledge Graphs, Semantic AI & Machine Learning, Enterprise Data
Integration, Linked Data & Data Publishing, Semantic Search,
Recommendation Services, Thesaurus and/or Ontology Management, Text
Mining, Data Mining and any related fields. All submissions should have
a strong focus on real-world applications beyond the prototypical stage
and demonstrate the power of semantic systems!
= Important Dates:
* Paper Submission Deadline: May 25, 2020 (11:59
pm,Hawaii time)
* Notification of Acceptance: June 15, 2020 (11:59 pm,
Hawaii time)
* Camera-Ready Presentation: August 24, 2020 (11:59
pm, Hawaii time)
Submit your presentations here:
http://2020-eu.semantics.cc/submission-industry-presentations
== Workshops and Tutorials ==
Workshops and Tutorials at SEMANTiCS 2018 allow your organisation or
project to advance and promote your topics and gain increased
visibility. The workshops and tutorials will provide a forum for
presenting widely recognised contributions and findings to a diverse and
knowledgeable community. Furthermore, the event can be used as a
dissemination activity in the scope of large research projects or as a
closed format for research and commercial project consortia meetings.
= Important Dates for Workshops:
* Proposals WS Deadline: March 23, 2020 (11:59 pm,
Hawaii time)
* Notification of Acceptance: April 20, 2020 (11:59 pm,
Hawaii time)
= Important Dates for Tutorials (and other meetings, e.g. seminars,
show-cases, etc., without call for papers):
* Proposals Tutorial Deadline: May 11, 2020 (11:59 pm,
Hawaii time)
* Notification of Acceptance: June 01, 2020 (11:59
pm, Hawaii time)
== Special Calls ==
Special calls or sub-topics are dedicated towards specific topics that
are of special interest to the SEMANTiCS community. In case we receive a
sufficient amount of high quality submissions these topics will become
special tracks within the conference program. For 2020 SEMANTiCS
Amsterdam encourages submissions to the following sub-topics:
* Special Sub-Topic: Digital Humanities and Cultural Heritage
* Special Sub-Topic: LegalTech
* Special Sub-Topic: Blockchain and Semantics
Each sub-topic is managed by a distinct committee and encourages
submissions from the scientific or industrial domain. Scientific
submissions will undergo a thorough review process and will be published
in the conference proceedings in case of acceptance. Industrial
submissions will be evaluated and selected according to the quality
criteria of the industry track. We are looking forward to your submissions!
= Read a detailed description of all available calls online:
https://2020-eu.semantics.cc/calls
Hi,
Does anyone know a way to find out how many wikimedia users are active
globally compared to active on metawiki?
This mean they've made more than 5 edits in the last 30 days for this.
Thanks,
RhinosF1
Some near to mid-term changes that might be useful for everyone chiming in:
* Active Editors across all wikis is a metric we're working on, and it will
be part of Wikistats 2 sometime this fiscal year
* The new mediawiki history dataset will let you download data for all
wikis and crunch these numbers and much more:
https://dumps.wikimedia.org/other/mediawiki_history/readme.html (we're
close to publishing this but there's sample data for last August)
Maybe a little showcase talk is in order once the above two are completed?
On Mon, Jan 6, 2020 at 5:09 PM Nuria Ruiz <nruiz(a)wikimedia.org> wrote:
> >I was looking to try and work out what percent lf the active wikimedia
> community are participating on meta and comparing to another wiki farm. Any
> thoughts on that?
> I think it will help to give a bit of an example of why you are looking to
> find this information, why is it important. Participating in a wiki
> includes other things besides editions (translations for or software
> commits to features used on that one wiki, for example) so a precise
> comparison of one wiki ecosystem to the rest is quite a task.
>
> On Mon, Jan 6, 2020 at 9:58 PM Jonathan Morgan <jmorgan(a)wikimedia.org>
> wrote:
>
>> (Last reply to both lists; sorry for the spam)
>>
>> This sounds like it'd be a bit of work to build, and I don't think there
>> are curated datasets to help out. I think you would need to...
>>
>> 1. get the count of active editors on Meta for [PERIOD OF TIME]. Easy.
>> 2. perform a query or parse dumps to get the *list *of active editors
>> from every individual Wikimedia project for the same [PERIOD OF TIME]. Hard.
>> 3. de-duplicate that list (since many people edit multiple wikis in a
>> given say, month, and you don't want to overcount). Pretty easy.
>> 4. compare the resulting all-projects count with the Meta-only count.
>> Easy.
>>
>> This sounds like a lot of work to me! Again, there might be tools or
>> resources for this that already exist, but I'm not aware of them.
>>
>> It seems like having topline/platform-level counts for active editors
>> could be useful, as a dashboard or a public dataset. You might try requesting
>> this as a feature
>> <https://phabricator.wikimedia.org/maniphest/task/edit/?title=Wikistats%20Ne…>
>> for WikiStats. The worst they can say is "no", or "not yet" :)
>>
>> - J
>>
>>
>> On Mon, Jan 6, 2020 at 12:34 PM RhinosF1 - <rhinosf1(a)gmail.com> wrote:
>>
>>> Hi,
>>>
>>> I’ve just seen the replies and thanks to everyone whose replied.
>>>
>>> I was looking to try and work out what percent lf the active wikimedia
>>> community are participating on meta and comparing to another wiki farm.
>>> Any
>>> thoughts on that?
>>>
>>> RhinosF1
>>>
>>> On Mon, 6 Jan 2020 at 20:31, Aaron Halfaker <aaron.halfaker(a)gmail.com>
>>> wrote:
>>>
>>> > It doesn't look like Active Editors works for all wikis. I think you'd
>>> > have to merge activity across all wikis to get a stat like that. I'm
>>> not
>>> > sure I know of a good data strategy to get that.
>>> >
>>> > If you were to query it with quarry, you'd need to write a query for
>>> every
>>> > wiki and then write some code to merge the results. Oof.
>>> >
>>> > If you to extract it from the XML dumps, you'd need to process each
>>> Wiki
>>> > separately and then merge the results. Oof.
>>> >
>>> > The best solution to this is to have a common table/relation across all
>>> > Wikis and to aggregate from there. I don't think there's any such
>>> > cross-wiki table/relation available.
>>> >
>>> > On Mon, Jan 6, 2020 at 1:38 PM Jonathan Morgan <jmorgan(a)wikimedia.org>
>>> > wrote:
>>> >
>>> > > Same dashboard, but for "All wikis":
>>> > > https://stats.wikimedia.org/v2/#/all-projects
>>> > >
>>> > > That work?
>>> > >
>>> > > - J
>>> > >
>>> > > On Mon, Jan 6, 2020 at 11:32 AM RhinosF1 - <rhinosf1(a)gmail.com>
>>> wrote:
>>> > >
>>> > > > Hi,
>>> > > >
>>> > > > That provides active users for meta but not globally. Anything for
>>> > > global?
>>> > > >
>>> > > > RhinosF1
>>> > > >
>>> > > > On Mon, 6 Jan 2020 at 18:10, Jonathan Morgan <
>>> jmorgan(a)wikimedia.org>
>>> > > > wrote:
>>> > > >
>>> > > > > RhinosF1,
>>> > > > >
>>> > > > > Are you looking for information like this
>>> > > > > <https://stats.wikimedia.org/v2/#/meta.wikimedia.org>, or
>>> something
>>> > > > > different?
>>> > > > >
>>> > > > > - J
>>> > > > >
>>> > > > > On Mon, Jan 6, 2020 at 8:51 AM RhinosF1 - <rhinosf1(a)gmail.com>
>>> > wrote:
>>> > > > >
>>> > > > > > Hi,
>>> > > > > >
>>> > > > > > Does anyone know a way to find out how many wikimedia users
>>> are
>>> > > active
>>> > > > > > globally compared to active on metawiki?
>>> > > > > >
>>> > > > > > This mean they've made more than 5 edits in the last 30 days
>>> for
>>> > > this.
>>> > > > > >
>>> > > > > > Thanks,
>>> > > > > > RhinosF1
>>> > > > > > _______________________________________________
>>> > > > > > Analytics mailing list
>>> > > > > > Analytics(a)lists.wikimedia.org
>>> > > > > > https://lists.wikimedia.org/mailman/listinfo/analytics
>>> > > > > >
>>> > > > >
>>> > > > >
>>> > > > > --
>>> > > > > Jonathan T. Morgan
>>> > > > > Senior Design Researcher
>>> > > > > Wikimedia Foundation
>>> > > > > User:Jmorgan (WMF) <
>>> > https://meta.wikimedia.org/wiki/User:Jmorgan_(WMF)
>>> > > >
>>> > > > > (Uses He/Him)
>>> > > > > _______________________________________________
>>> > > > > Wiki-research-l mailing list
>>> > > > > Wiki-research-l(a)lists.wikimedia.org
>>> > > > > https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>> > > > >
>>> > > > _______________________________________________
>>> > > > Wiki-research-l mailing list
>>> > > > Wiki-research-l(a)lists.wikimedia.org
>>> > > > https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>> > > >
>>> > >
>>> > >
>>> > > --
>>> > > Jonathan T. Morgan
>>> > > Senior Design Researcher
>>> > > Wikimedia Foundation
>>> > > User:Jmorgan (WMF) <
>>> https://meta.wikimedia.org/wiki/User:Jmorgan_(WMF)>
>>> > > (Uses He/Him)
>>> > > _______________________________________________
>>> > > Wiki-research-l mailing list
>>> > > Wiki-research-l(a)lists.wikimedia.org
>>> > > https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>> > >
>>> > _______________________________________________
>>> > Wiki-research-l mailing list
>>> > Wiki-research-l(a)lists.wikimedia.org
>>> > https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>> >
>>> _______________________________________________
>>> Wiki-research-l mailing list
>>> Wiki-research-l(a)lists.wikimedia.org
>>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>>
>>
>>
>> --
>> Jonathan T. Morgan
>> Senior Design Researcher
>> Wikimedia Foundation
>> User:Jmorgan (WMF) <https://meta.wikimedia.org/wiki/User:Jmorgan_(WMF)>
>> (Uses He/Him)
>>
>> _______________________________________________
>> Analytics mailing list
>> Analytics(a)lists.wikimedia.org
>> https://lists.wikimedia.org/mailman/listinfo/analytics
>>
> _______________________________________________
> Analytics mailing list
> Analytics(a)lists.wikimedia.org
> https://lists.wikimedia.org/mailman/listinfo/analytics
>
Dear Wikimedia Researchers,
I am writing to you from the Berkman Klein Center for Internet & Society at Harvard University<https://cyber.harvard.edu/> - a public interest research center dedicated to exploring, understanding, and shaping the development of the digitally-networked environment. We are now accepting fellowship applications for the 2020-2021 academic year through our annual open call<https://cyber.harvard.edu/getinvolved/fellowships/2021Fellows>.
This fellowship opportunity is for those who wish to spend 2020-2021 in residence in Cambridge, MA as part of the Center's vibrant community of research and practice, and who seek to engage in collaborative, cross-disciplinary, and cross-sectoral exploration of some of the Internet's most important and compelling issues. Some more information is below, and I invite you to check out our full call<https://cyber.harvard.edu/getinvolved/fellowships/2021Fellows>, which has more information about our community activities and the application process.
Please feel most welcome to share this information with others in your network who may have interest. Any questions can be directed to 2021opencall(a)cyber.harvard.edu<mailto:2021opencall@cyber.harvard.edu>.
Applications will be accepted until Friday January 31, 2020 at 11:59 p.m. Eastern Time.
More about the fellowship program:
Fellows are supported in an inviting and playful intellectual environment - we have community activities designed to foster inquiry and risk-taking, to identify and expose common threads across fellows’ individual activities, and to bring fellows into conversation with the students, staff, faculty, and broader community at the Berkman Klein Center.
We invite applications from people working on a broad range of opportunities and challenges related to Internet and society, which may overlap with ongoing work at the Berkman Klein Center and may expose our community to new opportunities and approaches. We encourage applications from scholars, practitioners, innovators, engineers, artists, and others committed to understanding and advancing the public interest who come from —and have interest in — countries industrialized or developing, with ideas, projects, or activities in all phases on a spectrum from incubation to reflection.
To make fellowships a possibility for as wide a range of applicants as possible, in the 2020-2021 academic year we will award a small number of stipends to incoming fellows. This funding is intended to support people from communities who are underrepresented in fields related to Internet and society, who will contribute to the diversity of the Berkman Klein Center’s research and activities, and who have financial need. More information about this funding opportunity may be found here<https://cyber.harvard.edu/getinvolved/fellowships/stipends-for-candidates-2…>.
The work and well-being of the Berkman Klein Center for Internet & Society are profoundly strengthened by the diversity of our network and our differences in background, culture, experience, national origin, religion, sexual orientation, gender, gender identity, race, ethnicity, age, ability, and much more. We actively seek and welcome people of color, women, the LGBTQIA+ community, persons with disabilities, and people at intersections of these identities, from across the spectrum of disciplines and methods.
The full call for applications may be found at: https://cyber.harvard.edu/getinvolved/fellowships/2021Fellows
Applications will be accepted until Friday January 31, 2020 at 11:59 p.m. Eastern Time.
About the Berkman Klein Center for Internet & Society
The Berkman Klein Center for Internet & Society at Harvard University is dedicated to exploring, understanding, and shaping the development of the digitally-networked environment. A diverse, interdisciplinary community of scholars, practitioners, technologists, policy experts, and advocates, we seek to tackle the most important challenges of the digital age while keeping a focus on tangible real-world impact in the public interest. Our faculty, fellows, staff, and affiliates conduct research, build tools and platforms, educate others, form bridges and facilitate dialogue across and among diverse communities. More information at https://cyber.harvard.edu<https://cyber.harvard.edu/>.
Feel free to reach out to me to chat informally, if you're interested in pursuing this endeavor.
best,
Dariusz
--
_____________________________
[https://lh3.googleusercontent.com/28_4liQwIiNQmYh0G9FjIw5_4xyXPU6AQlm3IeESn…]<https://nerds.kozminski.edu.pl>
Dariusz Jemielniak, Ph.D., Full Professor, head of MINDS<https://nerds.kozminski.edu.pl/>
(Management in Networked and Digital Societies), Kozminski University
Polish Academy of Sciences corresponding member
associate faculty Berkman-Klein Center for Internet and Society<https://cyber.harvard.edu>, Harvard University
Key books: Collaborative Society<https://mitpress.mit.edu/books/collaborative-society> (2020, MIT Press, with A. Przegalinska), Thick Big Data<https://global.oup.com/academic/product/thick-big-data-9780198839705?cc=gb&…> (2020, Oxford University Press), Common Knowlege?<https://www.sup.org/books/title/?id=24010> (2014, Stanford University Press)
Recent articles:
Jemielniak D. (2019) Wikipedia: Why is the common knowledge resource still neglected by academics?<https://academic.oup.com/gigascience/article/8/12/giz139/5651107>, Gigascience 8(12): giz139
Hergueux, J. & Jemielniak, D. (2019) Should digital files be considered a commons? Copyright infringement in the eyes of lawyers<https://www.tandfonline.com/doi/full/10.1080/01972243.2019.1616019?fbclid=I…>, The Information Society, 35(4): 198-215
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