WikiRevolutions: Collective memory building of North African uprisings in Wikipedia

Michela Ferron, University of Trento
Paolo Massa, Fondazione Bruno Kessler

Since December 2010, a series of pro-democracy uprisings have shocked North Africa, starting with Tunisia and spreading to Egypt, Algeria, Lybia, Lebanon and other countries, and eventually led to the overthrown of Ben Ali and Mubarak in Tunisia and Egypt, and to the death of Gaddafi in Lybia. As these events occurred in the streets, thousands of people provided their contributions to the related articles on Wikipedia.

In this research, presented at Wikisym 2011, we propose to study the formation of collective memories of these events, intended as the continuous active process of sense-making and negotiation between past and present. One of the most interesting Web 2.0 platforms for the study of collective memory processes is Wikipedia, built by the voluntary work of millions of people, and whose pages can be created and modified by anyone.

Focusing mainly on the Egyptian revolution, we argue that the heavy activity on Wikipedia about the recent North African uprisings can be interpreted as the beginning of collective memory building processes. Indeed, the article 2011 Egyptian revolution was created the same day the protests started. During the first 45 days it received an average of 135 edits each day by 1190 users (for comparison, the average number of edits per day for a random Wikipedia article is largely smaller than 1), while the associated talk page received an average of 61 edits per day by 282 users. The article is on Wikipedia in 49 different languages, and was accessed at least 900,000 times during the month of February 2011, confirming the popularity of Wikipedia for online consultation and information gathering.

Number of edits per day to the "2011 Egyptian revolution" article and talk page - From WikiChanges

If we focus on the amount of edits in time, we can observe that during the very first days the article “2011 Egyptian revolution” and its talk page received a large share of activity, with an average of almost 524 edits per day from 28 January to 2 February 2011 in the article, and about 235 edits per day from 29 January to 3 February 2011 in the talk page. In both the article and the talk page edit activity increased on 11 February 2011, when Mubarak resigned. Similarly, edit activity increased on the pages about the Tunisian revolution, where edits to the article raised from 88 on 14 January to 192 the day after, and edits to the talk page went from 5 on 13 January to 23 and 33 on 14 January and 15 January 2011, when Saudi Arabia announced to be hosting the former Tunisian president Ben Ali.

The study of editors’ collaboration in the formation of collective memoris can also take advantage of Wikipedia as a source of social network data. For example, conversations occurred in the talk pages can be analyzed exploiting social network analysis (SNA), interpreting the communicative interactions between users as ties between nodes in a network. In the network graph,  nodes are Wikipedia users and a directed edge is drawn from user A to B if A has replied to B in the talk page (we thank David Laniado for providing the network data, details can be found in this paper). The size of nodes depends on their betweenness centrality, which can be interpreted as the potential of a node for control over the information flow, while the color represents the number of edits to the article page. So, a large and dark node represents a user who is both very central in the network and contributed heavily to the article.

In the network, the most central nodes (such as The Egyptian Liberal) are also the ones who performed most of the edits to the article, suggesting that heavily involved users tend to be very active both on the article and on the talk page. However, the graphical representation of the network can be useful to identify atypical users, such as Silver seren and Athinker. Silver seren has a high betweenness centrality, meaning that he is very active on the talk page, but is also very light in color, meaning that he did not edit the article very much. Indeed, this unusual behavior is explained by the user in the talk page, where he describes himself as the “reference guy”, who finds references but does not edit the article. Athinker is characterized by a marked difference between his indegree of 9, the number of replies he received, and his outdegree of 0, meaning that he did not replied to anyone. Indeed, he started 9 different threads on the talk page with opinionated statements but never took part in the discussions which were originated. By complementing networks of discussions occurring in Wikipedia with the content of users interactions it is possible to get a more complete picture of the dynamics involved in the creation of the collective memories. For instance, we are currently implementing automated content analysis tools such as PYWC, an open source software built on Pennebaker’s Linguistic Inquiry and Word Count, to explore the patterns of language used in Wikipedia pages related to traumatic events.

Another research direction for the study of collective memories in Wikipedia is related to cross-cultural studies. For example, it would be interesting to analyze how two or more language communities form their memories about the same events. To this regard, we developed Manypedia, a web tool which can compare two different language versions of the same page. Currently Manypedia automatically translates both pages into one among 56 possible languages, adding some descriptive data. Our future work will also be aimed at integrating Manypedia with additional information extracted with PYWC, such as the levels of different emotions expressed in the text of the pages under comparison.

In this contribution we aimed at suggesting different research possibilities to empirically study the formation of collective memories. We believe Wikipedia offers an unprecedented opportunity for researchers for studying how we, as a society, build our cultural representations of the past, also through SNA and natural language processing techniques.

For more, see our full paper, Collective memory building in Wikipedia: The case of North African uprisings.

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About Michela Ferron

Michela Ferron is a PhD student at the Center for Mind/Brain Sciences of the University of Trento and collaborates with the SoNet (Social Networking) research group at IRST (Institute for Scientific and Technological Research) at Bruno Kessler Foundation (FBK) in Trento, Italy. Her research interests vary from cognitive and social psychology to the study of social aspects of Web 2.0. At the moment she is studying the formation of collective memories on the Web.