Why Wikipedia is good for the Economy - Trend Forecasting Through Wikipedia Editor Behavior

The more active Wikipedia Editors a country has, the better is the health of it's economy!

Different national cultures are reflected in Wikipedia editor behavior. In a hierarchical culture like Japan, there are a few senior Wikipedia editors who keep a tight rein on who is allowed to edit articles. In a more egalitarian culture like Sweden, a much higher percentage of active Wikipedia editors obtain the coveted Wikipedia Admin status.

In this project we find a relationship between intrasocial capital of countries and the structure of the Wikipedias of the matching European languages. In the context of the current economic crisis we compare success of an economy with the Wikipedia editor behavior of the corresponding country. The German, French, Italian, Polish, Dutch, Greek, Swedish, and Finnish languages are predominantly spoken in just the mother country, allowing for a one-to-one mapping between Wikipedia in that language and economy of the mother country. We obtained different metrics reflecting Wikipedia structure for each of these languages on July 5, 2012: total number of articles, total number of edits, the number of all users, and the number of active users (i.e. editors who have performed an edit in the last 30 days).

As our first measure of success of an economy we take intrasocial capital in the form of the corruption index by country from http://www.transparency.org/country. Scores range from 0 (highly corrupt) to 10 (very clean). As a second measure of success we take the sovereign credit default swap (CDS) rate the countries have to pay for 5-year protection on a default on their loans on July 5, 2012. The table above contains the basic numbers. For our comparisons, we normalize the Wikipedia metrics: total number of articles, total number of edits, the number of all users, and the number of active users are divided by the population of the country, to get the number of articles, total number of edits, number of all users, and number of active users per 1000 inhabitants per country.
The picture above visually illustrates the strong correlation between intrasocial capital measured through the corruption index, and the number of active Wikipedia users per 1000 inhabitants (WAusersNorm). The message is really strong: the more active Wikipedia editors a country has in proportion to its population, the less corrupt it is. The correlation table below confirms this picture for all measures we have been collecting.
The total number of Wikipedia articles (wikinorm), total number of edits (weditnorm), number of all users (wusernorm), and number of active users (wausernorm) per 1000 inhabitants per country are all significantly correlated with corruption. Even more, the number of active users (wausernorm) is correlated with the CDS rate. The more active Wikipedia editors a country has, the lower is the CDS rate the country’s central bank has to pay to protect its debts for the next 5 years.

Regressing the total number of Wikipedia articles (wikinorm), total number of edits (weditnorm), number of all users (wusernorm), and number of active users (wausernorm) against the dependent variable “corruption” leads to an adjusted R2 of 0.91 with the only predictor “wausernorm”. The same regression for the dependent variable CDS_rate leads to an adjusted R2 of 0.53 with the only predictor “wausernorm”. This means that 91% of the corruption in a country can be explained with the number of active Wikipedia editors. Similarly, 53% of the CDS rate of the country can be explained by the number of active Wikipedia editors. The key insight is as surprising as it is flattering for the most active Wikipedia editors: the higher the proportion of active Wikipedia editors in a country is, the less corrupt and the more financially stable is the country. This also leads to a clear recommendation for politicians: motivate your compatriots to become active Wikipedia editors!

Comments

Post a Comment

Popular posts from this blog

Predicting Stock Market Indicators Through Twitter “I hope it is not as bad as I fear”

Image
We have been working on trying to predict market indicators for quite some time by analyzing Web Buzz , predicting who will win an Oscar, or how well movies do at the box office . Among other things we have correlated posts about a stock on Yahoo Finance and Motley’s Fool with the actual stock price, predicting the closing price of the stock on the next day based on what people say today on Yahoo Finance, on the Web and Blogs about a stock title. The rising popularity of twitter gives us a new great way of capturing the collective mind up to the last minute. In our current project we analyze the positive and negative mood of the masses on twitter, comparing it with broad stock market indices such as Dow Jones, S&P 500, and NASDAQ. We collected the twitter feeds from one whitelisted IP for six months from March 30, 2009 to Sept 4, 2009, ranging from 5680 to 42820 tweets per day. According to twitter this corresponds to a randomized subsample of about one hundredth of the full volum...
Read more

My life in Alternative Realities - fatherlanders and nerds don’t go well together

Image
We are all living in different alternative realities, people with different personalities see reality from very different perspectives, potentially leading to a lot of friction and misunderstandings. “Nerds” are open to change, they believe in the progress of technology and innovation. “Fatherlanders” abhor change, they like tradition and authority, valuing the fatherland above all, and would like to reestablish the good old times. “Spiritualists” believe into supernatural forces, they are religious, meditate and hope that the forces of nature will heal their ailing. “Treehuggers” believe into sustainability and global warming, they want to save nature by restricting technical progress. I experience  this friction frequently in my daily life. As a computer and technology nerd with spiritualist and treehugger inclinations, my communication with members from other tribes sometimes does not end well.  My interactions with officers of the US Department of Homeland Security and the...
Read more

How Blind Trust in Generative AI Undermines Creative Work

Image
This summer, we experienced firsthand the damage caused by blind faith in the "superhuman" capabilities of generative AI, even among otherwise intelligent individuals. Here's what happened. We submitted a research paper to an academic conference, and after it was accepted, I paid the registration fee, booked flights, and arranged accommodations. A week later, we received an abrupt email from the organizers stating that our paper had been rejected. The reason? Their AI-based plagiarism and ChatGPT-detection tool flagged it as containing both plagiarized content and text generated by ChatGPT. This accusation was entirely unfounded. Our paper presented highly original work by our team, proposing novel AI algorithms to predict animal emotions—a concept never explored before. We detailed the development of an AI model to validate this approach, something completely unique to our research. By its very nature, it was impossible for our work to be plagiarized or generated by Chat...
Read more