It has been hypothesized that known words in the lexicon strengthen newly formed representations of novel words, resulting in words with dense neighborhoods being learned more quickly than words with sparse neighborhoods. Tests of this hypothesis in a connectionist network showed that words with dense neighborhoods were learned better than words…

This dissertation aims to develop the Generator of the Event Structure Lexicon (GESL) which is a tool to automate annotating the event structure of verbs in text to support textual inference tasks related to lexically entailed subevents. The output of the GESL is the Event Structure Lexicon (ESL), which is a lexicon of verbs in text which includes…

Three studies test the link between word order in binomials and psychological and demographic characteristics of a speaker. While linguists have already suggested that psychological, cultural and societal factors are important in choosing word order in binomials, the vast majority of relevant research was focused on general factors and on broadly…

Spatial language constitutes part of the basic fabric of language. Although languages may have the same number of terms to cover a set of spatial relations, they do not always do so in the same way. Spatial languages differ across languages quite radically, thus providing a real semantic challenge for second language learners. The essay first…

Analyzing the rate at which languages change can clarify whether similarities across languages are solely the result of cognitive biases or might be partially due to descent from a common ancestor. To demonstrate this approach, we use a simple model of language evolution to mathematically determine how long it should take for the distribution over…

Several models of language acquisition have emerged in recent years that rely on computational algorithms for simulation and evaluation. Computational models are formal and precise, and can thus provide mathematically well-motivated insights into the process of language acquisition. Such models are amenable to robust computational evaluation,…

The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's "cognitive plausibility." We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition…

This paper represents an attempt to conduct a corpus-based stylistic analysis of two conceptual metaphors in "The Unbearable Lightness of Being," which is a novel written by Milan Kundera. "Soul-body" and "lightness-heaviness" metaphors are foregrounded as being central themes all through the novel. The way such…

This study aims to evaluate the translation quality of two machine translation systems in translating six different text-types, from English to Persian. The evaluation was based on criteria proposed by Van Slype (1979). The proposed model for evaluation is a black-box type, comparative and adequacy-oriented evaluation. To conduct the evaluation, a…

The present study, situated in the area of variational pragmatics, contrasts tag question (TQ) use in Ireland and Great Britain using spoken data from the Irish and British components of the International Corpus of English (ICE). Analysis is on the formal and functional level and also investigates form-functional relationships. Findings reveal…

The article seeks to demonstrate the contribution that corpus linguistic software can make in news frame analysis and how it can help address some of the methodological challenges in the extraction of news frames. With the employment of corpus linguistic software WordSmith, the study conducts an inductive frame analysis of the UK press coverage of…

The field of topic modeling has become increasingly important over the past few years. Topic modeling is an unsupervised machine learning way to organize text (or image or DNA, etc.) information such that related pieces of text can be identified. This paper/session will present/discuss the current state of topic modeling, why it is important, and…

Dictionary studies have suggested that nearly half of the English lexicon have multiple meanings. It is not yet clear, however, if second language learners reading English texts will encounter words with multiple meanings to the same degree. This study investigates the use of words with multiple meanings in an authentic English novel. Two samples…

Cybercriminals are increasingly using Internet-based text messaging applications to exploit their victims. Incidents of deceptive cybercrime in text-based communication are increasing and include fraud, scams, as well as favorable and unfavorable fake reviews. In this work, we use a text-based deception detection approach to train models for…

This study investigates a possible way to analyze chat data from collaborative learning environments using epistemic network analysis and topic modeling. A 300-topic general topic model built from TASA (Touchstone Applied Science Associates) corpus was used in this study. 300 topic scores for each of the 15,670 utterances in our chat data were…