Multimodal Characterization of Emotion within Multimedia Space

Technological advancement and its omnipresent connection have pushed humans past the boundaries and limitations of a computer screen, physical state, or geographical location. It has provided a depth of avenues that facilitate human-computer interaction that was once inconceivable such as audio and body language detection. Given the complex modularities of emotions, it becomes vital to study human-computer interaction, as it is the commencement of a thorough understanding of the emotional state of users and, in the context of social networks, the producers of multimodal information. This study first acknowledges the accuracy of classification found within multimodal emotion detection systems compared to unimodal solutions. Second, it explores the characterization of multimedia content produced based on their emotions and the coherence of emotion in different modalities by utilizing deep learning models to classify emotion across different modalities.Comment: 8 pages, Published in International Conference on Computers and Computation (COMPUTE 2022), November 03-04, 2022, San Francisco, United State

Simulating trait evolution for cross-cultural comparison

Cross-cultural anthropologists have increasingly used phylogenetic methods to study cultural variation. Because cultural behaviours can be transmitted horizontally among socially defined groups, however, it is important to assess whether phylogeny-based methods—which were developed to study vertically transmitted traits among biological taxa—are appropriate for studying group-level cultural variation. Here, we describe a spatially explicit simulation model that can be used to generate data with known degrees of horizontal donation. We review previous results from this model showing that horizontal transmission increases the type I error rate of phylogenetically independent contrasts in studies of correlated evolution. These conclusions apply to cases in which two traits are transmitted as a pair, but horizontal transmission may be less problematic when traits are unlinked. We also use the simulation model to investigate whether measures of homology (the consistency index and the retention index) can detect horizontal transmission of cultural traits. Higher rates of evolutionary change have a stronger depressive impact on measures of homology than higher rates of horizontal transmission; thus, low consistency or retention indices are not necessarily indicative of ‘ethnogenesis’. Collectively, these studies demonstrate the importance of using simulations to assess the validity of methods in cross-cultural research

Comparative methods for studying cultural trait evolution: A simulation study

Anthropologists and archaeologists increasingly use phylogenetic methods to test hypotheses involving cross-cultural traits, but the appropriateness of applying tree-based methods to analyze cultural traits is unclear. The authors developed a spatially explicit computer simulation model to investigate trait evolution in relation to phylogeny and geography and used the simulation to assess the sensitivity of two comparative methods (independent contrasts and partial Mantel tests) to different degrees of horizontal transmission. Simulation results show that (a) the method of independent contrasts is sensitive to even small amounts of horizontal transmission in cultural data sets, (b) Mantel tests fail to cleanly discriminate between datasets characterized by different levels of horizontal and vertical trait transmission, and (c) partial Mantel tests do not produce markedly improved statistical performance when testing for associations among traits (as compared to independent contrasts). The results highlight the need for empirical estimates of horizontal transmission and extinction rates in cross-cultural datasets