Luis Terán

A fuzzy recommender system for eElections

eDemocracy aims to increase participation of citizens in democratic processes through the use of information and communication technologies. In this paper, an architecture of recommender systems for eElections using fuzzy clustering methods is proposed. The objective is to assist voters in making decisions by providing information about candidates close to the voters preferences and tendencies. The use of recommender systems for eGovernment is a research topic used to reduce information overload, which could help to improve democratic processes.

Maturity Model for Cognitive Cities

The key mission of cognitive cities is to bring into symbiotic cooperation the government, citizens, and the business. To achieve this, cutting-edge information technologies are used to build smarter cities (cognitive cities) in which administrations stand as principal providers for smart services to citizens, constructed communication between business/industry, and more efficient city governance. As a result, citizens, businesses and government are empowered with information that eases the relations between these three parties and the inclusion of cognitive processes for decision-making. This chapter focuses on the interaction between administrations and citizens. It highlights an eGovernment framework through which eEmpowerment of citizens can be achieved via the promotion of citizens’ participation. With the help of information technologies, such as geolocation, the Internet of things, and open source software and hardware, among others, smooth communication between government and citizens can be established, thus facilitating the decision-making processes in cognitive cities. The illustration of three different applications of intelligent agents shows how the eParticipation of citizens can be increased. The first case explains how collaborative working environments are used in the public sector for a collaborative legislation process, to support people in a virtual space in a time- and place-independent manner in the creation of an organic law. The second application illustrates how eDemocracy processes can be facilitated with the help of a so-called social voting advice application, which takes into consideration trust values among citizens and governmental representatives. Finally, the third application highlights how civic participation can be enhanced through building communities of interest and communities of practice within the SmartParticipation platform.

Dynamic Profiles Using Sentiment Analysis for VAA's Recommendation Design

Abstract In the context of elections, the Internet opens new and promising possibilities for parties and candidates looking for a better political strategy and visibility. In this way they can also organize their election campaign to gather funds, to mobilize support, and to enter into a direct dialogue with the electorate. This paper presents an ongoing research of recommender systems applied on e-government, particularly it is an extension of so-called voting advice applications (VAA’s). VAA’s are Web applications that support voters, providing relevant information on candidates and political parties by comparing their political interests with parties or candidates on different political issues. Traditional VAA’s provide recommendations of political parties and candidates focusing on static profiles of users. The goal of this work is to develop a candidate profile based on different parameters, such as the perspective of voters, social network activities, and expert opinions, to construct a more accurate dynamic profile of candidates. Understanding the elements that compose a candidate profile will help citizens in the decision-making process when facing a lack of information related to the behavior and thinking of future public authorities. At the end of this work, a fuzzy-based visualization approach for a VAA design is given using as a case study the National Elections of Ecuador in 2013.

Who You Should Not Follow: Extracting Word Embeddings from Tweets to Identify Groups of Interest and Hijackers in Demonstrations

In the latest years, a number of citizen movements and protests have spread across the world. One of the characteristics of such events is that demonstrations have been aroused by the use of social networking channels such as Twitter, Facebook, and Whatsapp, among others. Different scholars are currently analyzing this phenomenon to better understand its impact on societies. Furthermore, the use of the Internet as a driver or tool for organizing different groups and demonstrations leaves traces of social changes that have been addressed by technology. Nevertheless, it is important to define ways of identifying different movements, as well as possible misuse by so-called Internet trolls or hijackers, whose objective is to start arguments and confuse or upset other users. In this work, the authors present the case of demonstrations in Ecuador from March 2015 to April 2016 and use data from Twitter users who engaged in those demonstrations. Ecuador has a long history of demonstrations against different governments, which makes this scenario very attractive for more in depth study. Moreover, the authors present a framework for identifying political interest groups as well as possible hashtag hijackers. Specifically, this work focuses on the problem of giving recommendations to groups in which a group of users with the same political view receives suggestions of users they should not follow because they have opposing political views but use hijacked hashtags. Experiments on real-world data collected from the previously mentioned demonstrations show the effectiveness of this approach in automatically identifying hijackers so that they can be effectively recommended to a group as people they should not follow.

Public collaborative legislation: A case study of the ingenios act

Collaborative working environments have commonly been used by companies which also use information and communication technologies that allow synchronous and asynchronous real time interactions between individuals who share common objectives and work. These strategies have proven to be very effective for the private sector and can be adopted by public administration to encourage participation from citizens and eventually result in empowerment of societies. In this paper, a case study on public collaborative legislation, termed Wiki Legislation, is used for the analysis and development of an Act. The Act generated during the implementation of this project aims to integrate the systems of Science, Technology, Innovation and Ancestral Knowledge with Education, Higher Education and Culture in Ecuador. In this work, the design of the project, as well as a user-centered evaluation was conducted. Recommendations on how to enhance the development of future collaborative legislation projects are provided.

Evaluation of Visualization of a Fuzzy-Based Recommender System for Political Community-Building☆

Abstract Recommender systems are mainly used to reduce information overload and to provide recommendations of products likely to interest a user when given some information about his profile and preferences. The use of recommender systems on eGovernment is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on eGovernment services. In this work, the evaluation of visualization provided by a fuzzy-based recommender system for stimulating political participation and collaboration is proposed, using different evaluation methods for dimensionality reduction and fuzzy clustering algorithms that are the core of the recommender system approach. The results and recommendations given in this work are used for the implementation of the SmartParticipation project for the creation of political/thematic groups, which assumes that profiles of citizens and candidates cannot be considered unique items, but, rather are dynamic.

A literature review for recommender systems techniques used in microblogs

Abstract Online social networks (OSNs) are receiving great attention from the research community for different purposes, such as event detection, crisis management, and forecasting, among others. The increasing amount of research conducted with social networks opens the need for a classification methodology regarding trends in the field. This work does not cover all types of social networks; it focuses on the analysis of microblogs as a data source in the context of recommender systems (RSs). The main goal of this work is to provide authors with insights on the trends of academic literature reviews in the proposed context and to provide a comparison of different research approaches. The authors searched for up-to-date research papers related to RS methods using microblogs within a time period of five years, from 2012 to January 2018. Starting from 2012, a significant amount of research related to the subject field of RSs was conducted and identified by the authors of this work. After the filtering process, 39 papers were finally selected from journals and conferences in four different databases related to Internet technologies (i.e., IEEE, ACM, Science Direct, and Springer). A general classification presented in this work is then adopted and used to describe state-of-the-art social network recommendation approaches for microblogging. This work can be extended in the future to include novel methodologies and trends of RSs for microblogs.

Geospatial collective intelligence for health planning: A case study for screening tests in the city of Esmeraldas, Ecuador

Health planning via intelligent system developments is used to strengthen health care access, focusing on rural areas and underserved populations. In this paper, the authors identify, through a geospatial collective intelligence approach, suitable areas for the allocation of equipment, supplies, and services of health-screening tests for pregnant women in the city of Esmeraldas, Ecuador, with the objective of improving the territorial distribution of health services in Ecuador. The exercise was hosted with various interdisciplinary specialists in HIV from the Ministry of Public Health of Ecuador to determine by anonymous consensus the appropriate areas. The experts were provided with a software tool including features of GDSS and SDSS, from which automation provides the incorporation of the spatial version of the Delphi method in the location the location of health services. The results show that this approach had a high level of participation and feedback, which allowed obtaining the expected geoconsensus level, including high relevance and adequacy, with the proposed approach. This study provides empirical evidence on how the use of an interdisciplinary group of experts made it possible to determine a geoconsensus to allocate equipment in order to expand the coverage of screening tests of HIV in pregnant women in the city of Esmeraldas, Ecuador.

Applying Dynamic Profiles on Voting Advice Applications

In the context of elections, Information Systems (IS) open new and promising possibilities for parties and candidates looking for a better political strategy and visibility. In this way they can also organize their election campaign to gather funds, to mobilize support, and to enter into a direct dialogue with the electorate. This chapter presents an ongoing research of recommender systems applied on e-government, particularly it is an extension of so-called voting advice applications (VAA’s). VAA’s are Web applications that support voters, providing relevant information on candidates and political parties by comparing their political interests with parties or candidates on different political issues. Traditional VAA’s provide recommendations of political parties and candidates focusing on static profiles of users. The goal of this work is to develop a candidate profile based on different parameters, such as the perspective of voters, social network activities, and expert opinions, to construct a more accurate dynamic profile of candidates. Understanding the elements that compose a candidate profile will help citizens in the decision-making process when facing a lack of information related to the behavior and thinking of future public authorities. Then, a fuzzy-based visualization approach for a VAA design is given using as a case study the National Elections of Ecuador in 2013. At the end of this work, an existing Web-based application so-called Participa Inteligente is presented. It was developed for stimulating citizens participation in the context of the Ecuador National Elections 2017. It applies the concepts of Dynamic Profiles presented in this work.