Posted by & filed under Member Publications.

The (randomly) selected focus publication for August 2018 is:

Simchon, A., & Gilead, M. (2018). A Psychologically Informed Approach to CLPsych Shared Task 2018. In Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic (pp. 113-118).


This paper describes our approach to the CLPsych 2018 Shared Task, in which we attempted to predict cross-sectional psychological health at age 11 and future psychological distress based on childhood essays. We attempted several modeling approaches and observed best cross-validated prediction accuracy with relatively simple models based on psychological theory. The models provided reasonable predictions in most outcomes. Notably, our model was especially successful in predicting out-of-sample psychological distress (across people and across time) at age 50.


Posted by & filed under Executive Posts, Member Opportunities.

[From Karolina Hansen]

For many of us, summer is a time for writing. Why not to publish in Psychology of Language and Communication? The journal is peer-reviewed, open-access, and free for authors (thanks to the University of Warsaw covering the costs). It is published by DeGruyter (now Sciendo), indexed in many databases, ranked by CiteScore, and has SCImago Journal Rank (SJR) and Source Normalized Impact per Paper (SNIP). For more information, check the website ( or contact Karolina Hansen (, who is an associate editor of the journal.

Posted by & filed under Member Publications.

The (randomly) selected focus publication for July 2018 is:

Burgoon, J.K., Dunbar, N. E., & Giles, H. (2017). Interaction coordination and adaptation. In J.K. Burgoon, N. Magnenat-Thalmann, M. Pantic, & A. Vinciarelli (Eds.), Social signal processing (pp. 78-96). Cambridge, UK: Cambridge University Press.

Download a PDF of this chapter here.

Posted by & filed under Member Publications.

The (randomly) selected focus publication for June 2018 is:

Boyd, R. L., & Pennebaker, J. W. (2017). Language-based personality: A new approach to personality in a digital world. Current Opinion in Behavioral Sciences, 18, 63–68.

Personality is typically defined as the consistent set of traits, attitudes, emotions, and behaviors that people have. For several decades, a majority of researchers have tacitly agreed that the gold standard for measuring personality was with self-report questionnaires. Surveys are fast, inexpensive, and display beautiful psychometric properties. A considerable problem with this method, however, is that self-reports reflect only one aspect of personality—people’s explicit theories of what they think they are like. We propose a complementary model that draws on a big data solution: the analysis of the words people use. Language use is relatively reliable over time, internally consistent, and differs considerably between people. Language-based measures of personality can be useful for capturing/modeling lower-level personality processes that are more closely associated with important objective behavioral outcomes than traditional personality measures. Additionally, the increasing availability of language data and advances in both statistical methods and technological power are rapidly creating new opportunities for the study of personality at ‘big data’ scale. Such opportunities allow researchers to not only better understand the fundamental nature of personality, but at a scale never before imagined in psychological research.