No abstract

Crowdsourced civic engagement is a novel form of democratic participation that allows citizens to share their ideas and deliberate in a multitude of diverse participatory processes that are emerging all over the world, influencing, often with binding power, urban plans, city budgets, and even legislation, among many other forms of public policy decisions. As a result, hundreds of thousands of civic contributions are produced as ideas, comments, and proposals circulate among citizens and between them and government officials, generating an avalanche of mostly unstructured data, which decision-makers have difficulty to manage. Sentiment analysis techniques have the potential to process and classify these contributions in ways that can make it easier to make sense of them. In this paper, we present the design and implementation of a rule based sentiment analyzer that integrates a lexicon, optimized for the Spanish language and the application domain of civic contributions. We present the results of our first evaluation and discuss the aspects of the proposal that have room for improvement in future work.