Proceedings of the Annual Meeting of the Cognitive Science Society

As time series analysis continues to capture the interest of cognitive and behavioral researchers, it is increasingly important to evaluate these methods and compare their respective insights. Here, we evaluate three popular analyses: vector autoregression, cross-correlation, and cross-recurrence quantification analysis. Using social cohesion data derived from Twitter and daily counts of real-world events during the Arab Spring, we present a case study using these methods and evaluate their benefits, limitations, and differences in results. We propose that researchers interested in time series analysis consider these differences and use multiple methods to assure reliability of their results.