Can Network Analysis Techniques help to Predict Design Dependencies? An Initial Study

The degree of dependencies among the modules of a software system is a key attribute to characterize its design structure and its ability to evolve over time. Several design problems are often correlated with undesired dependencies among modules. Being able to anticipate those problems is important for developers, so they can plan early for maintenance and refactoring efforts. However, existing tools are limited to detecting undesired dependencies once they appeared in the system. In this work, we investigate whether module dependencies can be predicted (before they actually appear). Since the module structure can be regarded as a network, i.e, a dependency graph, we leverage on network features to analyze the dynamics of such a structure. In particular, we apply link prediction techniques for this task. We conducted an evaluation on two Java projects across several versions, using link prediction and machine learning techniques, and assessed their performance for identifying new dependencies from a project version to the next one. The results, although preliminary, show that the link prediction approach is feasible for package dependencies. Also, this work opens opportunities for further development of software-specific strategies for dependency prediction.Comment: Accepted at ICSA 201

Features for Detecting Aggression in Social Media: An Exploratory Study

Cyberbullying and cyberaggression are serious and widespread issues increasingly affecting Internet users. With the “help" of the widespread of social media networks, bullying once limited to particular places or times of the day, can now occur anytime and anywhere. Cyberaggression refers to aggressive online behaviour intending to cause harm to another person, involving rude, insulting, offensive, teasing or demoralising comments through online social media. Considering the gravity of the consequences that cyberaggression has on its victims and its rapid spread amongst internet users (specially kids and teens), there is an imperious need for research aiming at understanding how cyberbullying occurs, in order to prevent it from escalating. Given the massive information overload on the Web, it is crucial to develop intelligent techniques to automatically detect harmful content, which would allow the large-scale social media monitoring and early detection of undesired situations. Considering the challenges posed by the characteristics of social media content and the cyberaggression task, this paper focuses on the detection of aggressive content in the context of multiple social media sites by exploring diverse types of features. Experimental evaluation conducted on two real-world social media dataset showed the difficulty of the task, confirming the limitations of traditionally used features.Sociedad Argentina de Informática e Investigación Operativ

Semantic enrichment of social annotations for Web resource classification

Social annotations voluntarily provided by users in tagging or book-marking sites such as Delicious or Flickr have been recognized as an interesting source of metadata for assisting tasks such as classification of Web resources. However, the open-ended nature of the tags employed to annotate resources leads to problems such as the introduction of noise and ambiguity that may hinder clas- sification results. This paper presents an approach for semantically analyse social annotations in order to attain enriched, concept-based representations of Web resources. Experimental results showed that the strategies proposed to relate tags to conceptual entities allow to improve the results of resource classification.Sociedad Argentina de Informática e Investigación Operativ

On the Role of Personality Traits in Followee Recommendation Algorithms

Followee recommendation is a problem rapidly gaining importance in Twitter and other micro-blogging communities. Most traditional recommendation systems only rely on content or topology, disregarding the effect of psychological characteristics over the followee selection process. As personality is considered one of the primary factors that influence human behaviour, this study aims at assessing the impact of personality in the accurate prediction of followees. It analyses whether user personality could condition followee selection by combining personality traits with the most common followee recommendation factors.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Hacia una e-Participación efectiva: Un análisis de la interacción y compromiso de los ciudadanos digitales en Argentina

La democracia y los procesos políticos formales dependen fundamentalmente de una comunicación eficaz con los ciudadanos y de la toma de decisiones informada sobre temas públicos. La e-Participación puede ser entendida como el proceso de involucrar en los procesos de la administración pública a los ciudadanos a través de las tecnologías de la información y la comunicación. De esta forma, fomentar la eParticipación requiere conocer cómo tanto los entes gubernamentales como los ciudadanos se expresan e interactúan en los diferentes medios de comunicación. Luego, este conocimiento hará posible la definición de estrategias de comunicación más efectivas, dando lugar a un proceso de toma de decisiones sobre temas públicos participativo, inclusivo, y colaborativo. En este contexto, este trabajo estudia y caracteriza por un lado cómo los entes gubernamentales se manifiestan en los medios sociales y sus distintas formas de transmitir información; y por otro cómo los ciudadanos interactúan y manifiestan su compromiso con los entes. Particularmente, el estudio se enfoca en los entes municipales de la Provincia de Buenos Aires en Argentina, por ser la que concentra la mayor cantidad de ciudadanos del país.Democracy and formal political processes fundamentally depend on the effective communication with citizens, and on informed decision making on public issues. E-participation can be understood as the process of involving citizens in political aspects of the public administration through information and communication technologies. In this way, promoting e-Participation requires knowing how both governmental entities and citizens express themselves and interact in the different media. Then, this knowledge will allow the definition of more effective communication strategies, giving rise to a participatory, inclusive, and collaborative decision-making process of public issues. In this context, this work studies and characterizes how government entities manifest themselves in social media and their different ways of transmitting information; and how citizens interact and express their commitment to the government entities. Particularly, the study focuses on the local government entities of the province of Buenos Aires in Argentina, as it concentrates the largest number of citizens in the country.Fil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentin

On the Role of Personality Traits in Followee Recommendation Algorithms

Followee recommendation is a problem rapidly gaining importance in Twitter and other micro-blogging communities. Most traditional recommendation systems only rely on content or topology, disregarding the effect of psychological characteristics over the followee selection process. As personality is considered one of the primary factors that influence human behaviour, this study aims at assessing the impact of personality in the accurate prediction of followees. It analyses whether user personality could condition followee selection by combining personality traits with the most common followee recommendation factors.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Ciudadanos digitales: explorando el rol de los medios sociales de comunicación en la e-participación

La democracia y los procesos políticos formales dependen fundamentalmente de una comunicación eficaz con los ciudadanos y de la toma de decisiones informada sobre temas públicos, teniendo los ciudadanos derecho a una participación igual e incluyente. La e-Participación puede ser entendida como el proceso de involucrar a los ciudadanos a través de las tecnologías de la información y la comunicación de forma que la administración pública sea participativa, inclusiva, colaborativa y deliberativa. En este contexto, surgen nuevas áreas de investigación referidas no solo a la aplicabilidad de las herramientas de participación electrónica, sino también a los mecanismos de interacción fomentados por Internet y los medios sociales. Dado que dichos medios podrían tener un rol preponderante en la participación ciudadana, este trabajo tiene como objetivo estudiar y caracterizar la presencia de los entes gubernamentales en los medios sociales de comunicación, y su relación con los ciudadanos. En particular, el objeto de estudio de este trabajo es la Provincia de Buenos Aires (Argentina), la cual concentra la mayor cantidad de ciudadanos del país, y por lo tanto presenta una gran necesidad de comunicación con ellos.Sociedad Argentina de Informática e Investigación Operativ