The Democracy Cube as a Framework for Guiding Participatory Planning for Community-based IT Initiatives

Literature suggests there is a need to build more theoretically-informed understandings of the social processes implicated in participatory IT planning and implementation (Jakku & Thorburn, 2010). In this study, we explore the value of Archon Fung’s (2006) “democracy cube” as a framework for qualitatively examining the process we undertook for planning a community-based IT strategy. Our planning process involved consultations with multiple stakeholder groups across five different communities, as well as from other entities involved in disaster management, with the aim of surfacing factors that shaped local communities’ abilities to participate in disaster management activities. These factors, drawn from qualitative interviews and categorized using a SWOT framework, were subsequently translated into an IT strategy. In this paper, we revisit this process and examine it using Fung’s (2006) three dimensions of democratic participation as a lens: participant selection (our use of multiple stakeholder groups); communication and decision (our consultation process); and authority and power (how participant input drove our strategy). We use the framework to identify the specific practices that made IT planning participative, as well as those that made it nonparticipative. We also use our empirical data to explore ways that the framework can be enhanced

Natural Language Database Interface for the Community Based Monitoring System

PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20-22, 200

Age and Gender Profiling of Social Media Accounts

The growth of social networking platforms such as Facebook and Twitter has bridged communication channels between people to share their thoughts and sentiments. However, along with the rapid growth and rise of the Internet, the idea of anonymity has also been introduced wherein user identities are easily falsified and hidden. Hence, presenting difficulty for businesses to give accurate advertisements to specific account demographics. As such, this study aims to identify gender and age group of Filipino social media accounts through analyzing post contents. Several features will be considered and various techniques will be adopted to process posts written in English, Filipino, and Taglish (Tagalog interspersed with English). The study will implement these techniques and record their compatibility and performance in a Filipino setting. A computational model capable of gender and age classification will be built as the final product

E-Participation towards Legislation: The Case of the Philippines

This paper discusses the issues toward the development of an eParticipation framework contextualized to the Philippine setting for legislation and the development of an ICT system. The project aims to enhance citizen participation and community empowerment in two key roles of the legislature – law making and executive oversight. The project used the concepts of eTransformation and Rapid Application Development Approach (RAD) to identify issues that will affect the future deployment of eParticipation Systems

Artificial Intelligence and its Potential Adverse Impacts on the Philippine Economy

Recent developments in artificial intelligence (AI) and deep learning techniques are expected to reshape the nature of the working environment in many economic sectors through the automation of many white collar jobs. This technological breakthrough poses threats of job obsolescence in several industries, particularly for a labor abundant country such as the Philippines. With human capital as one of its largest resources, the services sector is a major contributor to the country’s economy, contributing around 60% of the total gross domestic product and employing about 22.8 million workers (Philippine Statistics Authority, 2017)

Utilizing tweet content for the detection of sentiment-based interaction communities on Twitter

Community detection is one way of extracting insights from voluminous Twitter data. Through this technique, Twitter users can be grouped into different types of communities such as those who interact a lot, or those who have similar sentiments about certain topics. However, most works do not utilize tweet content and simply use directly available information like Twitter follows. Hence, this work explores the incorporation of hashtags and sentiment analysis (also taking into account conversational context) in the input graph for community detection through various schemes. Evaluation was performed by investigating the modularity score, topic similarity/variety, and sentiment homogeneity of the resulting communities. Results suggest that when compared to a baseline graph based on mentions, a scoring approach is more likely to yield a different set of communities compared to the more popular edge-weighting approach. Insights gleaned from the study show the importance of other evaluation methods (depending on the end-goal) aside from usual quantitative metrics of community network structure, and that community detection in conjunction with topic modeling can be a tool for analyzing Twitter discourse. © 2018 IEEE