She Said, She Said: A Conversation about Growing Education Research in Occupational Therapy

"He Said She Said" ― a Male/Female Corpus of Polish

Gender differences in language use have long been of interest in linguistics. The task of automatic gender attribution has been considered in computational linguistics as well. Most research of this type is done using (usually English) texts with authorship metadata. In this paper, we propose a new method of male/female corpus creation based on gender-specific first-person expressions. The meth...

He Said, She Said: Gender in the ACL Anthology

Studies of gender balance in academic computer science are typically based on statistics on enrollment and graduation. Going beyond these coarse measures of gender participation, we conduct a fine-grained study of gender in the field of Natural Language Processing. We use topic models (Latent Dirichlet Allocation) to explore the research topics of men and women in the ACL Anthology Network. We ...

He said, she said: demystifying the dreaded disciplinary hearing.

That's What She Said: Double Entendre Identification

Humor identification is a hard natural language understanding problem. We identify a subproblem — the “that’s what she said” problem — with two distinguishing characteristics: (1) use of nouns that are euphemisms for sexually explicit nouns and (2) structure common in the erotic domain. We address this problem in a classification approach that includes features that model those two characterist...

He said, she said: a quasi-signal detection analysis of daily interactions between close relationship partners.

In everyday life, close relationship partners enact behaviors through which they may influence each other. To understand how these exchanges affect partners, previous research has emphasized the enactors' reports, the receivers' perceptions, or the congruence of the two. We developed a strategy based on classic signal detection theory that combined elements from these three approaches in a natu...