Aspects of Risk Factors in Two Digital Art Festivals

The present study aims to highlight some risk factors in staging two digital art festivals, from the perspective of the organizers and of the audience. We corroborated the results of two questionnaires that were used following the 2018 editions of the Electro Arts Festival, centred on organizing artistic events resulted from the alignment of technology with visual images, music and dance, and Clujotronic, which included experimental and interdisciplinary installations projects with electronic music, visual art and independent digital games. Statistical correlations were found in the different types of risks and their triggering factors; the results indicated the interdependence between the two perspectives in assessing the events in question

Building a Twitter Sentiment Analysis System with Recurrent Neural Networks

This paper presents a sentiment analysis solution on tweets using Recurrent Neural Networks (RNNs). The method is can classifying tweets with an 80.74% accuracy rate, considering a binary task, after experimenting with 20 different design approaches. The solution integrates an attention mechanism aiming to enhance the network, with a two-way localization system: at memory cell level and at network level. We present an in-depth literature review for Twitter sentiment analysis and the building blocks that grounded the design decisions of our solution, employed as a core classification component within a sentiment indicator of the SynergyCrowds platform