Category Archives: Wikipedia

Which parties were most read on Wikipedia?

Taha and Stefano previously looked at the distribution of Wikipedia pages by candidate. These pages are much more patchy than Twitter handles: only in the Conservative and Labour cases do more than 40% of candidates have an account, whilst most other parties have far less (though we should note that we are relying on the data crowdsourced by YourNextMP, which is brilliant but not guaranteed to be perfectly accurate). This could be a mistake: the 520 candidates who did have a Wikipedia page together garnered 1.6 million views in the week before the election. Could the candidates who didn’t make have missed a trick? Again, the party leaders account for a lot of the traffic: David Cameron and Ed Miliband contribute around 400,000 of those views alone. But many other pages attracted several thousand views, which in the context of a closely contested election in constituencies of around 70,000 in size, could be quite significant. The distributions of page views by party are shown below.

Wikipedia-Bar

How do Wikipedia views compare to activity on Twitter? They are uncannily similar: they are highly correlated, and at around the same levels: on average, candidates which got 1,000 Twitter mentions got 1,000 Wikipedia views. Perhaps a surprise – considering the very different mechanisms which generate the data.

TwitterMentions-vsWikipedia

The question is of course: do these Wikipedia views make any difference to the local battles? Once we have the full results we can find out…

Online presence of the General Election Candidates: Labour wins Twitter while Tories take Wikipedia

Some have called the forthcoming UK general election a Social Media Election. It might be a bit of exaggeration, but there is no doubt that both candidates and voters are very active on social media these days and take them seriously. The Wikipedia-Shapps story of last week is a good example showing how important online presence is for candidates, journalists, and of course voters. We don’t know how important this presence is in terms of shaping the votes, but at least we can look into the data and gauge the presence of the candidates and the activity of the supporters. In this post and some others we present statistics of online activity of parties, candidates, and of course voters. For an example, see the previous post on the searching behaviour of citizens around the debate times.

Who is on Twitter?

Candidates and parties are very much debated by supporters on social media, particularly Facebook and Twitter. But how active are candidates themselves on these platforms? In this post we show simply how many candidates from each party and in which constituencies have a Twitter account. Some of them might be more active than others and some might tweet very rarely, and we will analyse this activity in the next posts. Here we count only who has any kind of publicly known account.

t_all_small

Geographical distribution of candidates who have Twitter account.

The figure above shows the geographical distributions of candidates for each party and whether they have a Twitter account. There are some interesting results in there. For example, Labour has the largest number of Twitter-active candidates, whereas ALL the SNP candidates tweet. While LibDem and Green parties have the same number of accounts, normalised by the overall number of constituencies that they are standing in, Green seems to be more Twitter-enthusiastic. UKIP loses the Twitter game both in absolute number and proportion.

Who is on Wikipedia?

Having a Twitter account is something of a personal decision.  A candidate decides to have one and it’s totally up to them what to tweet. The difference in the case of Wikipedia, is that ideally candidates would not create or edit one about themselves. Also the type of information that you can learn about a candidate on their Wikipedia page is very different to what you can gain by reading their tweets.

Geographical distribution of the candidates, whom Wikipedia has an article about.

Geographical distribution of the candidates, whom Wikipedia has an article about.

The figure above shows the constituencies that the candidates standing in are featured in the largest online encyclopaedia, Wikipedia. Here, Tories are the absolute winners, in terms of the number of articles. Greens are the least “famous” candidates and LibDem are well behind the big two. In the next post we will explore often voters turn to Wikipedia to learn about the parties and candidates, and I’m sure by reading that you’ll be convinced that being featured on Wikipedia is important!

Gender?

All right, so far, Labour won Twitter presence and Tories took Wikipedia (remember all the SNP’s also have a Twitter account). But how about the gender of the candidates? Is there any gender-related feature in social presence pattern of the candidates?

First let’s have a look at the gender distribution of the candidates.

Geographical distribution of the candidates colour-coded by gender.

Geographical distribution of the candidates colour-coded by gender.

As you see in the figure above, there are fewer female candidates than male ones across all the parties. Only 12% of the UKIP candidates are female while the Greens have the highest proportion at 38%. Tories sit right next to UKIP on the list of the most male oriented parties. There is also a clear pattern that most of the constituencies in the centre have male candidates.

How about social media?

Among all the candidates, 20% of male candidates are featured in Wikipedia, whereas this is about 17% for female candidates. Almost half of the Tories male candidates are in Wikipedia, whereas this goes down to 28% for their female counterparts. Only Labour female candidates have more coverage in Wikipedia compared to the males of the party, but the difference is marginal. ّIn all the other parties, males have a higher coverage rate. The tendency of Wikipedia to pay more attention to male figures is a very well known fact. 

Twitter is different. Slightly more female candidates (76%) have a Twitter account than male candidates (69%). Almost all (96%) of Labour females tweet, and Tory female candidates are more active than their male candidates. This pattern however is lost for the UKIP candidates, as 52% of their males are on Twitter compared to only 44% of their female candidates (who have the lowest rate among all the party-gender groups).

Data

The data that we used to produced the maps and figures come mainly from a very interesting crowd-sourced project called yournextmp. However, we further validated the data using the Wikipedia and Twitter API’s. If you want to have a copy, just get in touch!

Coverage of European parties in European language Wikipedia editions

By  and .

Reading niche political party Wikipedia pages, as one does when working on the Social Election Prediction project, one might wonder if there are any trends in which languages have articles about political parties of different countries. I did. Most major political parties in Europe have Wikipedia pages in dozens of languages, this makes sense, they are important, globally. But the same is not true for minority parties or party leaders. What does it mean that there are articles about this center-left Hungarian political alliance only in Czech, German, French, Flemish and Polish, in addition to Hungarian and English? Does the page of this ChristianUnion Dutch politician have coverage in Indonesian (in addition to German and English) because of the Netherlands’ long history with Indonesia?

We downloaded the data to find out.

We downloaded the data for European countries with a singular national language (or overly dominant singular language), so there would be something of a one-to-one relationship between language and country. We then grouped the countries in communities based on the number of links between the political party Wikipedia pages to minimize the inter-category and maximize the intra-category links.

Would countries cluster by historic ties? By geographical proximity? By political sympathies? Or would they just cluster completely randomly?

The first two observations that came from the graph were:

             1. Political Wikipedia is influenced by geography

Just look at the clusters grouped together by color – these are “communities” of languages, or countries that are closely interlinked.

Clusters of European country-languages based on the coverage of their political parties in Wikipedia editions of other languages.

Clusters of European country-languages based on the coverage of their political parties in Wikipedia editions of other languages.

            2. Everyone is reading about Greece

All of the news about Syriza, the 2015 Greek election and the possibility of a Grexit has apparently made fellow Europeans very interested in reading about Greek political parties. Greek political party pages have one of the highest rates of coverage among European parties.

The position of Greek parties is very special with a high rate of coverage in most of the other European languages.

The position of Greek parties is very special with a high rate of coverage in most of the other European languages.

            Stay tuned. More observations from this dataset to come.

 

This post has been cross-posted to the Oxford Internet Institute’s  Elections and the Internet blog.

Wikipedia and Shapps: Sockpuppetry, Conflict of Interest, or None?

Taha Yasseri

Will the real Grant Shapps please stand up? ViciousCritic/Totally Socks, (CC BY-NC-SA)

You must have heard about the recent accusation of Grant Shapps by the Guardian. Basically, the Guardian claims that Shapps has been editing his own Wikipedia page and “Wikipedia has blocked a user account on suspicions that it is being used by the Conservative party chairman, Grant Shapps, or someone acting on his behalf”.

In a short piece that I wrote for The Conversation I try to explain how these things work in Wikipedia, what they mean,  and basically how unreliable these accusations are.

There are two issues here:

First, conflict of interest, for which Wikipedia guidelines suggest that “You should not create or edit articles about yourself, your family, or friends.” But basically it’s more a moral advice, because it’s technically impossible to know the real identity of editors. Unless the editors disclose their personal information deliberately.

The second point is that the account under discussion is banned by a Wikipedia admin not because of conflict of interest (which is anyway not a reason to ban a user), but Sockpuppetry: “The use of multiple Wikipedia user accounts for an improper purpose is called sock puppetry”. BUT, Sockpuppetry is not generally a good cause for banning a user either. It’s prohibited, only when used to mislead the editorial community or violate any other regulation.

Sock puppets are detected by certain type of editors who have very limited access to confidential data of users such as their IP-addresses, their computed and operating systems settings and their browser. This type of editor is called a CheckUser, and I used to serve as a CheckUser on Wikipedia for several years.

In this case the accounts that are “detected” as sock puppets have not been active simultaneously — there is a gap of about 3 years between their active periods. And this not only makes it very hard to claim that any rule or regulation is violated, but also, for this very long time gap, it is technically impossible for the CheckUser to observe any relation between the accounts under discussion.

Actually, the admin who has done the banning admits that his action has been mostly because of behavioural similarity (similarity between the edits performed by the two users and their shared political interests).

Altogether, I believe the banning has no reliable grounds and it’s based on pure speculation, and also the Guardian accusations are way beyond what you can logically infer from the facts and evidence.

 

This post has been cross-posted to the Oxford Internet Institute’s  Elections and the Internet blog.

Brief History of Political Wikipedia

ParliamentEdits Wikipedia places among the top Google results for almost all topics – including political parties and politicians. This is why this Social Election Prediction Project exists; when voters seek information before an election they may turn to Wikipedia. Yet the earliest days of Wikipedia featured little political content. While the site itself was founded on January 11th 2001, the first page for a political party appears to be that for the Green Party of the United States, created months later, on September 19th 2001. Early contributors were perhaps more interested in, or more interested in spreading information about, fringe parties as fellow minority party the Libertarian Party in the United States also had a Wikipedia page before one was created for the Republican or Democratic parties. Today contributors are quick to update Wikipedia political pages after elections and there is even often a Wikipedia page dedicated to the election itself. Several weeks ahead of the UK General Election for example, the Wikipedia page for it is already thousands of words long, full of descriptions of the leader debate and various seat predictions. However, Wikipedia did not cover the UK General Election back in 2001. The pages for the Conservative and Labour parties were not created until well after the June election of that year. (Interestingly the pages for those two parties and the page for the Liberal Democrats were all created on the same day, October 11th 2001.) While Wikipedia might currently be a quickly updated source for political information, the medium’s open-editing policy has created some controversies as political figures around the world have been accused of favorably editing their own pages. In 2014, Hindustan Times covered a number of  Indian politicians with suspiciously clean Wikipedia pages ahead of state elections, writing “The profile of former Mayor and Shiv Sena corporator Shraddha Jadhav, who has been eyeing the Sion Koliwada assembly seat, mentions that she is known for her ‘elegant dressing’, her ‘fashion sense’ and ‘her crisp cotton sarees’, along with describing her as an articulate corporator.” but that the Wikipedia page “has no mention of the controversies that plagued her term as well as that she lost a by-poll she had contested in 2006.” The descriptors still remain on Jadhav’s page, perhaps because they are cited to an article from the Hindustan Times itself. In 2006, the Massachusetts newspaper the Lowell Sun reported that a staff member in the office of the U.S. Representative Marty Meehan had tried to replace the congressman’s entire Wikipedia page with a staff-written bio. Wikipedia political pages can be edited to troll as well as just to mislead. In 2014, users from inside the US Congress were briefly banned from editing Wikipedia altogether after a contributor added content that “accuse[d] Donald Rumsfeld of being an alien lizard and Cuba of faking the moon landings.” Tools such as ParliamentEdits and CongressEdits, in the UK and US respectively, help monitor politically motivated edits. The tools are automated Twitter accounts that tweet out anytime a user associated with an IP address within the legislatures edits Wikipedia. Inspired by the first such tool, ParliamentEdits, people have created similar Twitter bots for the legislatures in Australia, Israel and Greece. The openness of Wikipedia is what allows for political tampering but the site’s transparency is also then what enables watchdogs to pinpoint actors behind fishy edits. There are many countries where government officials hold influence over the press; but no information source that allows to users to trace the trail of the article creation as easily as Wikipedia.

 

This post has been cross-posted to the Oxford Internet Institute’s Elections and the Internet blog.

 

Ethics of Wikipedia Research

Ethics of Editing

The election results on this Wikipedia page are wrong, I can tell. As we collect data for the Social Election Prediction Project, I am reviewing many a Wikipedia political party page and every so often I see mistakes. For this project I am checking that the page exists, ensuring that the page existed before the date of the election so that a voter could have used it to find out political information beforehand. I am not, it should be noted, checking for accuracy of information. Yet sometimes there are errors that glare. As an occasional Wikipedia editor and a stickler for correcting errors, I feel a strong urge to correct the mistakes I come across. Yet, as an academic looking at this page in a research context I am hesitant to alter that which I am studying. What are the ethical boundaries for academics conducting research on Wikipedia?

In 2012, Okoli et al. wrote an overview of scholarship on Wikipedia, a huge and varied field, totaling almost 700 articles in peer-reviewed journals in disciplines ranging from Computer Science, to Economics to Philosophy (Okoli et al, 2012).  The Okoli article, titled, “The people’s encyclopedia under the gaze of the sages: A systematic review of scholarly research on Wikipedia,” is comprehensive on the subject of all Wikipedia research up to that date, but does not deal extensively with ethics. The ethical issues that are addressed are those that are linked with privacy concerns of studying the Wikipedia community. In their article on using wikis for research, Gerald Kane and Robert Fishman note that while all Wikipedia data is available under General Public License, or GPL, and so can be used without copyright concerns, researchers should still be cognizant of the privacy of Wikipedia editors (Kane & Fishman, 2009). For example many of the editors Kane and Fishman interacted with were hesitant to connect their real world identity with that of their identity on Wikipedia, and so did not want to conduct conversations through email or any other platform.

Of course, acting as a part of a community is not always a research taboo. Participatory action research, a method that arose from psychologist’s Kurt Lewin’s action research, emphasizes collaboration between researchers and the communities at hand. However, while participatory action research could apply for someone editing a Wikipedia article, studying the behavior of other editors and working with other editors to define the study, Wikipedia editors are not the subjects of the Social Election Prediction Project. The Social Election Prediction Project is a study of Wikipedia as an informational object. The subjects are voters seeking information before an election, and Wikipedia is simply a tool to help us measure their information-seeking behavior.

The ethical ambiguities of researching Wikipedia are just a symptom of Web 2.0., where everyone is a potential contributor. The same question could be asked of researchers studying Twitter for example, should they tweet? It depends on the objective of the study. For the Social Election Prediction Project, I have not edited any Wikipedia page that I am looking at for research purposes. While I could not alter the outcome for this specific project as we are looking at past elections and so historic page views, in some small way, improving political Wikipedia pages could make more people turn to Wikipedia for political news. However, I will continue to do minor edits for the Wikipedia pages I read in my own time. While not acting as researcher, I can be collaborator and reader both.

Kane, G., & Fichman, R. (2009). The Shoemaker’s Children: Using Wikis for Information Systems Teaching, Research, and Publication. Management Information Systems Quarterly, 33(1).
Okoli, C., Mehdi, M., Mesgari, M., Nielsen, F. Å., & Lanamäki, A. (2012). The People’s Encyclopedia Under the Gaze of the Sages: A Systematic Review of Scholarly Research on Wikipedia. Retrieved from http://papers.ssrn.com/sol3/Papers.cfm?abstract_id=2021326
This post has been cross-posted to the Oxford Internet Institute’s Elections and the Internet blog.

Subjectivity and Data Collection in a “Big Data” Project

SYRIZA

There remains a mistaken belief that qualitative researchers are in the business of interpreting stories and quantitative researchers are in the business of producing facts.” (boyd & Crawford, 2012) The Social Election Prediction project is once again in the data collection phase and we’re here to discuss some of the data collection decision points we have encountered thus far or, in other words, the subjective aspect of big data research. This is not to denigrate this type of quantitative research. The benefits of big data for social science research are too numerous to list here and likely any reader of this blog is more than familiar. In the era of big data, human behaviour that was previously only theorized is now observable at scale and quantifiable. This is particularly true for the topic of this project, information seeking behaviour around elections. While social scientists have long studied voting behaviour, historically they have had to rely on self-reported surveys for signals as to how individuals sought information related to an election.

Now, certain tools such as Wikipedia and Google Trends provide an outside indication as to how and when people search for information on political parties and politicians. However, although Wikipedia page views are not self-reported, this does not mean that they are objective. Wikipedia data collection requires the interjection of personal interpretation; the typical measure of subjectivity. These decisions tend to fall into two general categories: the problem of individuation and the problem of delimitation.

When is something considered a separate entity and when should it be grouped? The first is a frequently occurring question in big data collection. For this project, this question has reoccurred with party alliances and two-round elections. If we are collecting Wikipedia pages to study information-seeking behaviour related to elections, should we consider views only of the page of a party alliance or of the individual party as well? This is a problem of individuation, deciding when to consider discrete entities as disparate and when to count them as a single unit. The import of party alliances varies by country but big data collection necessitates uniformity for the analysis stage. So, a decision must be made. The same issue arises with two-round elections. Should they be considered as one election instance or two? Again, a uniform decision is necessary for the next step of data analysis.

For decisions of delimitation one must set a logical boundary on something continuous. Think, time. For the Social Election Prediction project, we are collecting the dates of all of the elections under consideration, so that we can compare the Wikipedia page views for the various political parties involved prior to the election. For most electoral systems, the date of an election is simple, but for countries like Italy and the Czech Republic with two-day elections, the question of when to end the information-seeking period arises. The day before the election begins? After the first day? There is uniform data solution to this question, only yet another subjective decision by the data collector.

In the article quoted above, boyd and Crawford question the objectivity of data analysis but the subjective strains in big data research begin even earlier, with the collection stage. Data is defined in the collection stage, and these definitions, as with the analysis, can be context specific. Social media research faces the same definitional problems but many of the collection decisions have already been made by social media platform. Of course, same criticisms could be raised about traditional statistical analysis as well. While there may be unique benefits to big data research, it faces many of the same problems as previous research methods. Big data often seen as some sort of “black box” but the process of building that box can be just as subjective as qualitative research.

 

This post has been cross-posted to the Oxford Internet Institute’s Elections and the Internet blog.