Editorial: Transactions on Affective Computing-Good Reasons for Joy and Excitement

IN its ninth year, the IEEE Transactions on Affective Computing (TAC) and Affective Computing as a field still enjoy an impressively uprising trend of interest both on the academic and the industrial side as is amongst others visible by the continuous new foundation of start-ups centred around the topic. At the same time, general trends in Artificial Intelligence (AI) are clearly visible also in Artificial Emotional Intelligence (AEI) these days. As an example, while the field of Affective Computing has been an early adopter of Deep Learning techniques such as long short-term memory recurrent neural networks as early as in 2008, the number of papers using Deep Learning has since risen roughly exponentially. Similarly, after the journal’s recent special issue now follows a first workshop on Affective Computing and Big Data, and in fact, one increasingly finds weakly supervised learning exploiting big social multimedia and other big data sources for training Affective Computing systems. The combination of increasingly sophisticated learning methods and exploitation of increasingly bigger data mark exciting times–not only for AI, but also for AEI, where one notices a similar boost in system performance and robustness as in many AI tasks these days. Good reasons for excitement and joy for the field, but also for TAC in several ways in the last months as follows. Particularly good news and reason for joy give the results compiled for the journal’s firsts IEEE periodic review and advisory committee exercise held every six years that showed a good rise in popularity by continuously increasing annual submission rates for the journal that has roughly doubled since its start while maintaining a low acceptance rate around 30 percent or as low as 25 percent, an outstanding gender-ratio in the editorial board, as the percentage of female associate editors of the journal exceeds the percentage of female members in the IEEE. Further, twice as high of a citation half-life value, and five times as high of an immediacy factor since the journal’s start were observed which impressively demonstrates how newly published articles get increasingly rapidly cited. Equally impressively, the journal Eigenfactor increased roughly by a factor two. Most importantly, however, the official latest 2016 Impact Factor (IF) has risen to 3.149. Likewise, the journal ranks number 32 out of 154 IEEE journals in the 2016 Journal Citation Report (JCR) by 5-year IF, and number 16 out of 133 for Computer Science-Artificial Intelligence in the 2016 JCR by 5-year IF, and number 3 for Computer ScienceCybernetics by the same measure. As the next good reason for joy and excitement, following the first ever award of the journal given at the Association for the Advancement of Affective Computing’s (AAAC) 2015 6 AAAC Affective Computing and Intelligent Interaction International Conference (ACII) where the Most Influential Papers of TAC since their beginning had been awarded, the journal now switched into giving regular awards: At the 7 ACII 2017 held in San Antonio, Texas, from 23 to 26 October 2017, for the first time a Best Paper in IEEE TAC since the (last) ACII was given. 75 papers were eligible from this period. After a pre-selection based on impact by citations, 11 candidate papers served as the basis for selection by 19 Associate Editors who were allowed to vote. We heartily congratulate the winners Mohammad Soleymani, Sadjad Asghari-Esfeden, Yun Fu, and Maja Pantic in appreciation of the authors’ original and impactful contribution to the field “Analysis of EEG Signals and Facial Expressions for Continuous Emotion Detection” as appeared in volume 7, number 1 of TAC.