Recommending Items in Social Tagging Systems Using Tag and Time Information

In this work we present a novel item recommendation approach that aims at improving Collaborative Filtering (CF) in social tagging systems using the information about tags and time. Our algorithm follows a two-step approach, where in the first step a potentially interesting candidate item-set is found using user-based CF and in the second step this candidate item-set is ranked using item-based CF. Within this ranking step we integrate the information of tag usage and time using the Base-Level Learning (BLL) equation coming from human memory theory that is used to determine the reuse-probability of words and tags using a power-law forgetting function. As the results of our extensive evaluation conducted on data-sets gathered from three social tagging systems (BibSonomy, CiteULike and MovieLens) show, the usage of tag-based and time information via the BLL equation also helps to improve the ranking and recommendation process of items and thus, can be used to realize an effective item recommender that outperforms two alternative algorithms which also exploit time and tag-based information.Comment: 6 pages, 2 tables, 9 figure

Campos literarios emergentes: literatura digital en América Latina / Emerging literary fields: Digital Literature in Latin America

El presente artículo analiza las prácticas de producción y recepción presentes en la literatura digital, a partir de dos obras digitales producidas por autores latinoamericanos: Word Toys de Belén Gache y Gabriella Infinita de Jaime Alejandro Rodríguez. El objetivo del análisis es dar a conocer el surgimiento de campos literarios relacionados con el uso y experimentación con las nuevas tecnologías de la comunicación e información, y discutir sus implicancias respecto a lo que proponemos como una nueva experiencia cultural.The article analyzes two digital works produced in Latin America: Word Toys by Belén Gache and Jaime Alejandro Rodríguez’s Gabriella Infinita. The aims of the article are to make visible the connections between emerging literary fields and the experimentation with the new technologies of information and communication, and discuss their status as new cultural experience

Towards Real-Time, Country-Level Location Classification of Worldwide Tweets

In contrast to much previous work that has focused on location classification of tweets restricted to a specific country, here we undertake the task in a broader context by classifying global tweets at the country level, which is so far unexplored in a real-time scenario. We analyse the extent to which a tweet's country of origin can be determined by making use of eight tweet-inherent features for classification. Furthermore, we use two datasets, collected a year apart from each other, to analyse the extent to which a model trained from historical tweets can still be leveraged for classification of new tweets. With classification experiments on all 217 countries in our datasets, as well as on the top 25 countries, we offer some insights into the best use of tweet-inherent features for an accurate country-level classification of tweets. We find that the use of a single feature, such as the use of tweet content alone -- the most widely used feature in previous work -- leaves much to be desired. Choosing an appropriate combination of both tweet content and metadata can actually lead to substantial improvements of between 20\% and 50\%. We observe that tweet content, the user's self-reported location and the user's real name, all of which are inherent in a tweet and available in a real-time scenario, are particularly useful to determine the country of origin. We also experiment on the applicability of a model trained on historical tweets to classify new tweets, finding that the choice of a particular combination of features whose utility does not fade over time can actually lead to comparable performance, avoiding the need to retrain. However, the difficulty of achieving accurate classification increases slightly for countries with multiple commonalities, especially for English and Spanish speaking countries.Comment: Accepted for publication in IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE

Networks of Collaboration and Creation in Latin American Digital Literature

In her article Networks of Collaboration and Creation in Latin American Digital Literature Carolina Gainza examines how production and reception of literature have been affected by digital technology, with special emphasis on issues related to Latin American digital literature. Gainza analyzes Jaime Alejandro Rodriguez\u27s Narratopedia, Doménico Chiappe\u27s La Huella de Cosmos, and Leonardo Valencia\u27s and Eugenio Tiselli\u27s El Libro Flotante in order to highlight collective practices of creation involved in digital productions. Through the discussion of these issues, Gainza offers an overview of ongoing changes wrought by digital technology in contemporary Latin American digital culture

The Analogue Technology of S: Exploring Narrative Form and the Encoded Mystery of the Margin

The 2013 publication of S, J.J. Abrams’ and Doug Dorst’s “love letter to the written word,” represents a particular intervention in the debates surrounding the future of the book and the relationship between analogue and digital publication. In S we see how the analogue nature of this particular book drives much of the narrative structure of the text, indeed the physical presentation of the book informs much of the imaginative contents of the narrative. In this article I would like to consider the theoretic bounds of this novel and its form, from the question of marginal (and fragmented) writing that is evoked in the work of Jacques Derrida, to the importance of the medium and the message that it carries as described by Marshall McLuhan. One could furthermore consider the manner in which S integrates itself into the imagination of the reader both in textual and in literal terms in light of Umberto Eco’s notion of the “open work.

The afterlife of "Little Women" as a feminist text

Maestría en Inglés con orientación en Literatura angloamericanaThis thesis closely examines the classic novel Little Women (1868) by Louisa May Alcott and three contemporary reworkings: Hasta siempre, Mujercitas (2004) by Marcela Serrano, The Little Women Letters (2012) by Gabrielle Donnelly and the manhwa Dear my girls (2005 to 2012) by Kim Hee-Eun. In relation to Little Women’s hypertexts: pastiche, sequel and adaptation, respectively, part of the analysis contemplates to what extent the texts both pay homage to their nineteenth-century predecessor and refurbish it for a more contemporary perspective from a postfeminist stance. Despite the fact that these texts were created in different settings and times, they reveal how the patriarchal authority prevailing in the past persists in this century. The main characters in each of them are strong and resilient women trying to survive in a hostile world. These stories come together as a political appeal for recognition to women who must be acknowledged and empowered.Fil: Lanzi, Elisabet Adriana. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina

First Women, Second Sex: Gender Bias in Wikipedia

Contributing to history has never been as easy as it is today. Anyone with access to the Web is able to play a part on Wikipedia, an open and free encyclopedia. Wikipedia, available in many languages, is one of the most visited websites in the world and arguably one of the primary sources of knowledge on the Web. However, not everyone is contributing to Wikipedia from a diversity point of view; several groups are severely underrepresented. One of those groups is women, who make up approximately 16% of the current contributor community, meaning that most of the content is written by men. In addition, although there are specific guidelines of verifiability, notability, and neutral point of view that must be adhered by Wikipedia content, these guidelines are supervised and enforced by men. In this paper, we propose that gender bias is not about participation and representation only, but also about characterization of women. We approach the analysis of gender bias by defining a methodology for comparing the characterizations of men and women in biographies in three aspects: meta-data, language, and network structure. Our results show that, indeed, there are differences in characterization and structure. Some of these differences are reflected from the off-line world documented by Wikipedia, but other differences can be attributed to gender bias in Wikipedia content. We contextualize these differences in feminist theory and discuss their implications for Wikipedia policy.Comment: 10 pages, ACM style. Author's version of a paper to be presented at ACM Hypertext 201