Yearly Archives: 2011

Qwiki: awesome animations of Wikipedia pages

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Some time ago I made a video of evolution in time of the Wikipedia page about 2005 London bombings.
Well, what you get from Qwiki, for almost every Wikipedia page, has nothing to do with it! It is awesome! Below there is the embedding of the qwiking of page about 2005 London bombings.

View 7 July 2005 London bombings and over 3,000,000 other topics on Qwiki.

Qwiki gets info from a Wikipedia page and automatically reads a text summary (synchronise with the text), adding images from different sources.
It is amazing! I can imagine students in schools pondering “instead of listening this boring professor about history of Europe, I’ll check the qwiking of it” (see below).

View History of Europe

Or do you want to quickly get an idea about the recent 2011 Egyptian revolution? Nothing better than qwiking it (see below).

View 2011 Egyptian revolution and over 3,000,000 other topics on Qwiki.

Well, you can compare these videos with the reports created by professional journalists of CNN or BBC and pondering how far we are from automatic generation in real-time of news reports.
Currently most videos are short (even when the corresponding pages are very long) and this totally makes sense from Qwiki perspective but I guess we are not far away from automatic generation of school lessons about geography, history or literature (and more). For example check the qwiking of the Trento, the city where I live and work.

View Trento and over 3,000,000 other topics on Qwiki.

And as an early feedbacker was saying, I’m nearly in tears. This is so beautiful.

Wikipedia datasets released

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I strongly believe in replicability of science and I tend to release all the datasets I work on for other people use, improvement and testing. This is what I’ve done when I was working on trust metrics and recommender systems (see the datasets I released on Trustlet.org time ago) and this is also what I do with the SoNet group now that we explore the social side of Wikipedia (see the datasets at http://sonetlab.fbk.eu/data/: they are social network extracted from User talk pages, data about activity patterns on Wikipedia pages, and also about social capital (not on Wikipedia)). Enjoy!

PhD Comics creator in Povo

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I work in Povo (Trento) and on April 28, 2001, at 4.00 pm, for the ICT International Doctoral School Welcome day, there will be Jorge Cham – Writer and artist of Piled Higher and Deeper (PhD Comics) “The power of procrastination”.
Below a comic made for the occasion. Translation for non-locals: “Pergine” is a small city close to Trento, “Teroldego” is a good local wine, “Spritz” is a local aperitif prepared with white or Prosecco wine, some Aperol or Campari, and sparkling mineral water. Actually there will be a free aperitif after the event, so what are you waiting?

… for your information, I since long reached the final state “hope they have a glass of Teroldego” ;)

“Social networks of Wikipedia” paper accepted at HyperText 2011

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The paper I wrote “Social networks of Wikipedia” got accepted for the 22nd ACM Conference on Hypertext and Hypermedia.If you are going to be as well in Eindhoven, on June 6-9, 2011, please let me know!
If you are interested, you can read the entire paper, the abstract is below. We also released the source code (Python) at sonetlab and released some network datasets extracted from User Talk pages (in GraphML format so you can easily import it in your tool, we like Gephi).


Network extracted from User Talk pages of Venetian Wikipedia visualized with Gephi.

Wikipedia, the free online encyclopedia anyone can edit, is a live social experiment: millions of individuals volunteer their knowledge and time to collective create it. It is hence interesting trying to understand how they do it. While most of the attention concentrated on article pages, a less known share of activities happen on user talk pages, Wikipedia pages where a message can be left for the specific user. This public conversations can be studied from a Social Network Analysis perspective in order to highlight the structure of the “talk” network. In this paper we focus on this preliminary extraction step by proposing different algorithms. We then empirically validate the differences in the networks they generate on the Venetian Wikipedia with the real network of conversations extracted manually by coding every message left on all user talk pages. The comparisons show that both the algorithms and the manual process contain inaccuracies that are intrinsic in the freedom and unpredictability of Wikipedia growth. Nevertheless, a precise description of the involved issues allows to make informed decisions and to base empirical findings on reproducible evidence. Our goal is to lay the foundation for a solid computational sociology of wikis. For this reason we release the scripts encoding our algorithms as open source and also some datasets extracted out of Wikipedia conversations, in order to let other researchers replicate and improve our initial effort.

Studying Collective Memories in Wikipedia

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I’m the supervisor of Michela Ferron, PhD student at the Center for Mind/Brain Sciences of the University of Trento and working with me in the SoNet group of the Bruno Kessler Foundation.
Her project is on formation of collective memories in Wikipedia and she just put up an interesting blog I suggest you to check. You find it at http://empiricalmemories.wordpress.com.

Below a video showing some comments posted during the fifth anniversary of September 11 attacks and during the first anniversary of the Virginia Tech massacre (occurred on 16 April 2007) on the related Wikipedia talk pages. But on the blog there is much more.

The state of Wikipedia

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www.thestateofwikipedia.com

The transcript is below:

Wikipedia is one of the most important websites on the Internet today, but you might be surprised to learn it began as a side project of another online encyclopedia. That was called Nupedia, to be a traditional encyclopedia written by experts—free and online—but only one person had final publishing authority and it wasn’t quite taking off.
As the founder of Nupedia, I led the group to establish a farm team of sorts for future Nupedia articles. We used a new software platform to make collaboration easy—the wiki—Wikipedia.
It happened to be the perfect way to write many pages very quickly. Soon enough, Nupedia couldn’t keep up and Wikipedia took center stage. We were creating not just a free content encyclopedia but a “free encyclopedia that anyone can edit.” Other language editions appeared quickly—over 270 at last count—and it was soon followed by sister projects like Wikisource, Wikinews and Wiktionary.
In 2003, I created the Wikimedia Foundation to ensure that Wikipedia could keep up with its own growth. Wikipedia gets almost 400 million visitors every month, and the list of sites visited more often is very short and very famous. Wikipedia celebrates its tenth anniversary in January 2011 and in these ten years has become one of the most popular websites in the world. I still lead the community and the Wikimedia Foundation helps us to make Wikipedia what it is today.
Who does edit Wikipedia? Over time, as many as 1.2 million people have contributed to Wikipedia. As of 2010, there are more than 11 million monthly edits to all Wikipedias in all languages. According to one survey, we have about twice the proportion of Ph.Ds compared to the general public. On the English Wikipedia almost 50% have no religion and 14.6% of French editors claim to believe in Pastafarianism. It would be fair to say that most Wikipedians are not average.
One reason, maybe, is that editing a single page is easy, but getting heavily involved is harder. The community is defined by more than 200 combined policies, guidelines and essays, to say nothing of the discussions and reviews, committees and noticeboards, WikiProjects and more. All the site content is decided by Wikipedia’s volunteer contributors. The Wikimedia Foundation has no editorial role whatsoever.
The Foundation’s job is to keep the servers running and the lights on, but there’s more to it than that. The Foundation is also growing Wikipedia’s presence worldwide—more data centers to speed up Wikipedia worldwide and even bringing its first office outside of the United States to India.
Wikipedia is already very popular in the West and in the North. A new challenge is going to be making Wikipedia available to the developing world, as well. The Foundation is a charity and runs entirely on donations—some from corporations and institutions, but the vast majority from its millions of editors and readers.
It’s incredible what has been accomplished already, but Wikipedia is far from done. As any reader knows, some articles are very good, but some are not. Wikipedia still needs a lot of work. Yet, this is a new challenge. Not just building an encyclopedia from scratch, but making it better: more accurate, more citations. Not just broad, but deep.
There’s never been anything like Wikipedia before, and its future horizon is very, very long. As Wikipedia enters its second decade, it’s up to all of us to make sure it gets even better.

Science is nothing more than a game: 8-Year-Olds Publish Scientific Bee Study

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A study, titled “Blackawton bees”, has been published by the peer-reviewed journal “Biology Letters”. And this is nothing new.
The notable fact is that authors are 25 8- to 10-year-old children (and 2 older guys, a neuroscientist and a teacher). Source: Wired.

The project grew out of a lecture Beau Lotto, a neuroscientist, gave at the school, where his son was a student. Lotto spoke about his research on human perception, bumblebees and robots, and then shared his ideas on how science is done: Science is nothing more than a game.

The principal finding of the paper is: ‘We discovered that bumble-bees can use a combination of colour and spatial relationships in deciding which colour of flower to forage from. We also discovered that science is cool and fun because you get to do stuff that no one has ever done before. (Children from Blackawton)’.

Lotto got problems in getting the paper published because of lack of citations and I think it’s comment to Wired is all too true and agreeable: “That’s what I tell my PhD students: Don’t do any reading. Figure out why you wake up in the morning, what you’re passionate about, and then read the literature. But don’t figure out what’s interesting based on what other people say.”
And the attitude of one of the author (10 years old at most) really strikes a chord: “I thought science was just like math, really boring,” he said. “But now I see that it’s actually quite fun. When you’re curious, you can just make up your own experiment, so you can answer the question.” This should be science but sometimes possibly we adults tend to forget it.

A brief review of the paper now. The paper is written with a refreshening style, containing gems such as “Once upon a time…” and “the puzzle . . .duh duh duuuuhhh” as or considerations such as “Otherwise they might fail the test, and it would be a disaster.”

The paper, after the “Once upon a time…” entry, starts with “People think that humans are the smartest of animals, and most people do not think about other animals as being smart, or at least think that they are not as smart as humans. Knowing that other animals are as smart as us means we can appreciate them more, which could also help us to help them.”
They go on with “After talking about what it is like to create games and how games have rules, we talked about seeing the world in different ways by wearing bug eyes, mirrors and rolled-up books. We then watched the David Letterman videos of ‘Stupid Dog Tricks’, in which dogs were trained to do funny things.”
And they brag a little bit about themselves which I think it’s good “Next, we too had to learn to solve a puzzle that Beau (a neuroscientist) and Mr Strudwick (our headteacher) gave us (which took an artificial brain 10 000 trials to solve, but only four for us)”
Then they describe the real experiments they devised and conducted scientifically and report the results. “This experiment is important, because, as far as we know, no one in history (including adults) has done this experiment before.”

And they conclude with “Before doing these experiments we did not really think a lot about bees and how they are as smart as us. We also did not think about the fact that without bees we would not survive, because bees keep the flowers going. So it is important to understand bees. We discovered how fun it was to train bees. This is also cool because you do not get to train bees everyday. We like bees. Science is cool and fun because you get to do stuff that no one has ever done before. (Bees—seem to—think!)”

Image by mitikusa released on Flickr under Creative Commons license.

Wikimedia Foundation is hiring!

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Wikimedia Foundation (which runs among others Wikipedia) is looking for creative, motivated people who want to work in a highly-collaborative environment. They are positions in 22 areas and many are open until April 17, 2011 so hurry up!
The positions are based in San Francisco, but in some cases may be open to the possibility of people working remotely.

Community:

Technology:

Global Development:

Finance, Administration and Legal:

Cross-cultural studies of Wikipedia

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Papers I’m aware of that compare different Wikipedias. Do you know of other investigations comparing Wikipedias?

“Cultural Differences in Collaborative Authoring of Wikipedia” [1] compared French, German, Japanese and Duch Wikipedia. They used content analysis methods on just the page “Game” from the different Wikipedias, i.e just 4 pages. Authors find some correlations between patterns of contributions (number of deleting actions, of adding actions, of corrective actions) and the four dimensions of cultural influences proposed by Hofstede (Power Distance, Collectivism versus Individualism, Femininity versus Masculinity, and Uncertainty Avoidance). They conclude thatcultural differences that are observed in the physical world also exist in the virtual world.
“Cross-cultural analysis of the Wikipedia community” [2] analyzed English, Hebrew, Japanese, and Malay. They used content analysis of 120 Wikipedia talk pages (randomly sampled among “user talk pages”, “article talk pages”, and “Wikipedia policies talk pages”) in 4 language Wikipedias that differ in size and culture: English (western, big), Hebrew (western, small), Japanese (eastern, big) and Malay (eastern, small). Authors find that “Courtesy” postings were more frequent in large than in small Wikipedias, and in Eastern than in Western (significant). This is probably connected to Hofstede’s high vs low power distance, because high politeness is associated with high power distance. Plus, in collectivistics/high power distance cultures relationships prevail over tasks. Other correlations were not significant.
“Issues of cross-contextual information quality evaluation — The case of Arabic, English, and Korean Wikipedia” [3] compared Arabic, English, and Korean Wikipedias. Authors used many different methods, including content analysis of featured articles and count of number of Internal Links, of edits, of Adjacent Pages, of Registered Users, … and applied multivariate statistical analysis in order to find correlations. Hofstede’s cultural dimension scores for the United States, South Korea and the Arab World were also used to assess pair-wise similarity of the Wikipedias at the cultural level. They conclude that different Wikipedia communities may have different models for quality.

“Conflictual Consensus in the Chinese Version of Wikipedia” [4] focuses on one single Wikipedia, the Chinese one, and compares point of regional differences of its contributors based on four regions of origin (Mainland, Hong Kong / Macau, Taiwan, and Singapore / Malaysia). Authors claim that the main issue threatening the potential growth of Chinese Wikipedia are not the internal conflicts, nor the external competition by Baidu Baike but the evolution of the newly established “Avoid Region-Centric Policy”.

“Analyzing Cultural Differences in Collaborative Innovation Networks by Analyzing Editing Behavior in Different-Language Wikipedias” [5] does not use manual content analysis but social network analysis as a lens for comparing English, German, Japanese, Korean, and Finish language Wikipedias finding a difference between egalitarian cultures such as the Finnish, and quite hierarchical ones such as the Japanese.

References

[1] Pfeil, U., Zaphiris, P. and Ang, C. S. 2006. Cultural Differences in Collaborative Authoring of Wikipedia. Journal of Computer-Mediated Communication, 12, 88–113.

[2] Hara, N., Shachaf, P., & Hew, K.F. 2010. Cross-cultural analysis of the Wikipedia community. Journal of the American Society for Information Science and Technology, 61(10), 2097–2108.

[3] Stvilia, B., Al-Faraj, A., & Yi, Y. 2009. Issues of cross- contextual information quality evaluation—The case of Arabic, English, and Korean Wikipedias. Library & Information Science Research, 31(4), 232-239.

[4] Liao, H. 2009. Conflictual Consensus in the Chinese Version of Wikipedia. IEEE Technology and Society Magazine.

[5] Nemoto, K. Gloor, P. 2010. Analyzing Cultural Differences in Collaborative Innovation Networks by Analyzing Editing Behavior in Different-Language Wikipedias. Proceedings of COINs 2010, Collaborative Innovations Networks Conference, Savannah GA, Oct 7-9, 2010

Diderot on the Encyclopédie

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Noting that it could not be the work of a single man, for no one man is capable of knowing everything, Diderot refutes the Jesuit argument that the task would never be completed by saying that time, energy, and genius make impossible tasks possible.

An encyclopedia ought to make good the failure to execute such a project hitherto, and should encompass not only the fields already covered by the academies, but each and every brand of human knowledge. This is a work that cannot be completed except by a society of men of letters and skilled workmen, each working separately on his own part, but all bound together solely by their zeal for the best interests of the human race and a feeling of mutual good will.

Wondering what Diderot would say about Wikipedia today…

Source: Historical Text Archive.