VisMillion: A novel interactive visualization technique for realtime big data The rapid increase of connected devices causes more and more data to be generated and, in some cases, this data needs to be analyzed as it is received. As such, the challenge of presenting streaming data in such way that changes in the regular flow can be detected needs to be tackled, so that timely and informed decisions can be made. This requires users to be able to perceive the information being received in the moment in detail, while maintaining the context. In this paper, we propose VisMillion, a visualization technique for large amounts of streaming data, following the concept of graceful degradation. It is comprised of several different modules positioned side by side, corresponding to different contiguous time spans, from the last few seconds to a historical view of all data received in the stream so far. Data flows through each one from right to left and, the more recent the data, the more detailed it is presented. To this end, each module uses a different technique to aggregate and process information, with special care to ensure visual continuity between modules to facilitate the analysis. VisMillion was validated through a usability evaluation with 21 participants, as well as performance tests. Results show that it fulfills its objective, successfully aiding users to detect changes, patterns and anomalies in the information being received.

VISTX: Experimenting with Interactive Stance and Sentiment Visualisation Usergenerated content online continues to grow rapidly, and with this it becomes more challenging to evaluate the general consensus on a trending topic. Even greater challenges are faced if one wishes to compare opinions across multiple topics, as it can be difficult to make comparisons and reach conclusions with large amounts of data in an intuitive manner. VISTX explores innovative methods of visualising opinion in terms of stance and sentiment using Twitter data from the SemEval2016 Stance Dataset and presents three types of interactive visualisations. We discuss the method of testing the visualisations for effectiveness with a small group of users, where time taken and the number of incorrect interpretations were measured for each user. We discuss the results, which indicate that the xe2x80x98circlepackingxe2x80x99 visualisation type may lead to quicker interpretations for five or more topics. Finally, we discuss the work needed to further solidify these initial findings.