Computational Psycholinguistics Research Articles

Concepts and experiments on psychoanalysis driven computing

This research investigates the effective incorporation of the human factor and user perception in text-based interactive media. In such contexts, the reliability of user texts is often compromised by behavioural and emotional dimensions. To this end, several attempts have been made in the state of the art, to introduce psychological approaches in such systems, including computational psycholinguistics, personality traits and cognitive psychology methods.In contrast, our method is fundamentally different since we employ a psychoanalysis-based approach; in particular, we use the notion of Lacanian discourse types, to capture and deeply understand real (possibly elusive) characteristics, qualities and contents of texts, and evaluate their reliability. As far as we know, this is the first time computational methods are systematically combined with psychoanalysis. We believe such psychoanalytic framework is fundamentally more effective than standard methods, since it addresses deeper, quite primitive elements of human personality, behaviour and expression which usually escape methods functioning at “higher”, conscious layers. In fact, this research is a first attempt to form a new paradigm of psychoanalysis-driven interactive technologies, with broader impact and diverse applications.To exemplify this generic approach, we apply it to the case-study of fake news detection; we first demonstrate certain limitations of the well-known Myers–Briggs Type Indicator (MBTI) personality type method, and then propose and evaluate our new method of analysing user texts and detecting fake news based on the Lacanian discourses psychoanalytic approach.

The Discriminatory Power of Lexical Context for Alternations: An Information-theoretic Exploration

This paper makes a very exploratory, tentative, and thinking-aloud kind of suggestion for the corpus-based analysis of alternation data. I start from the observation that studies of alternations/choices in particular in corpus linguistics have become increasingly sophisticated in terms of the statistical methods they employ and the number of predictors they involve. While the predictors employed come from many different levels of linguistic analysis – phonology, morphosyntax, semantics, pragmatics/ discoursal, textual, psycholinguistic, sociolinguistic, and others – they are usually contextual in nature, meaning they characterize the context of the choice the language user needs to make or has just made. However, one aspect of the context seems to be crucially underutilized when it comes to modeling speakers’ choices: the lexical context. In this paper, I build on recent work in computational psycholinguistics to: (a) define a lexical-distribution prototype of each of the (typically, but not necessarily, two) alternants of an alternation; and (b) compute the degree to which each instance of the alternation in question diverges from each of the prototypes. Then, (c) the values that all choices score on the divergences from each of the prototypes are entered as predictors to all others in statistical models to, minimally, serve as a variable that controls for whatever information is contained in the lexical context of an instance of speaker’s choice. I exemplify the approach and its sometimes amazing predictive power on the basis of a choice between near synonyms, two morphosyntactic alternations (preposition stranding vs. pied-piping and of- vs. s genitives), and a distinction between the functions of well.

Linguistics: The Garden and the Bush

Linguistics: The Garden and the Bush

What the Heck Is Salience? How Predictive Language Processing Contributes to Sociolinguistic Perception.

Some sociolinguistic variables are prone to hypercorrection, stigmatization and style shifting, while other variables are not. The status of the former type—sometimes called stereotypes and markers (Labov, 1972)—has been attributed to the increased meta-linguistic awareness language users seem to have of these variables. This awareness in turn is attributed to the salience of these variables, such that greater salience is assumed to cause greater meta-linguistic awareness (e.g., Trudgill, 1986). Salience has similarly been invoked when aiming to explain implicit social inferences about, or attitudes toward, speakers who exhibit certain variables in their speech (Babel, 2016; Drager and Kirtley, 2016; Squires, 2016). However, salience is a hard to define concept (for review, see Auer et al., 1998; Kerswill and Williams, 2002) and, partly as a consequence, “notoriously difficult to quantify” (Hickey, 2000). For a concept that plays such a central and ubiquitous role in sociolinguistic explanations, this is arguably a dangerous state of affairs. This motivates the present commentary. We believe that advances in computational psycholinguistics offer definitions of sociolinguistic salience that are more concrete, both empirically and formally grounded, and quantifiable (and thus falsifiable). We propose that it is important to distinguish between the initial salience a listener experiences when first encountering a novel variant (e.g., because of exposure to a previously unfamiliar dialect, sociolect, or idiolect—henceforth lects; Schirmunski, 1930; Preston, 1996), and salience at later stages. Salience after the initial encounter is the cumulative product of an individual's experience related to the lectal variant, including direct experience, as well as discourse about the variant (e.g., explicit stereotyping or enregisterment, Agha, 2003). Here we focus on the causes for initial salience, which we think can be defined in a principled and quantifiable way. Specifically, we propose that salience in the first moments when a novel lect is encountered cannot be understood without reference to prior expectations based on listeners' past language experience and the ensuing expectation violation that a listener experiences relative to those prior expectations—an idea explored in more depth by Racz (2012, 2013). Here we contribute to these efforts. We draw on basic concepts from probability and information theory to define initial salience as a function of (top-down) prior expectations. This has several advantages. First, the proposed definition of salience is quantifiable (see also Racz, 2013). Second, computational psycholinguistics has linked the very same quantities to language processing and learning. Recognizing this link offers the opportunity to ground sociolinguistic salience in human information processing—both empirically and theoretically—offering a parsimonious account of initial salience. After we have outlined our proposal, we briefly turn to an apparent puzzle that was raised during the workshop leading to this special issue: several presenters pointed out that salience sometimes seems to be inversely related to the frequency of a variant and other times positively related. This puzzle readily dissolves once the view proposed here is taken into account.

Flexible processing and the design of grammar.

We explore the consequences of letting the incremental and integrative nature of language processing inform the design of competence grammar. What emerges is a view of grammar as a system of local monotonic constraints that provide a direct characterization of the signs (the form-meaning correspondences) of a given language. This "sign-based" conception of grammar has provided precise solutions to the key problems long thought to motivate movement-based analyses, has supported three decades of computational research developing large-scale grammar implementations, and is now beginning to play a role in computational psycholinguistics research that explores the use of underspecification in the incremental computation of partial meanings.

Better Surface Realization through Psycholinguistics

AbstractIn this survey, we review recent progress on surface realization in natural language generation (NLG), highlighting how machine learning models have moved beyond n‐grams to successfully incorporate linguistic insights into increasingly rich models. We also advance the view that NLG still has much to gain by taking up insights from psycholinguistic studies – not only of human production but also of comprehension. We highlight how realization ranking models can be improved by modeling the role of memory in human language comprehension and discuss how surface realizers might transition to using grammars developed for incremental parsing in computational psycholinguistics, thereby making them more suitable for integration into real‐time incremental dialog systems. From a production standpoint, we suggest that the principle of uniform information density has the potential to enhance the theoretical basis for choice making in NLG and discuss two initial steps in this direction. Finally, we conclude our survey with a discussion of prospects for community‐based evaluation of surface realization systems.

Anaphoric one and its implications

The nominal anaphoric element one has figured prominently in discussions of linguistic nativism because of an important argument advanced by C. L. Baker (1978). His argument has been frequently cited within the cognitive and linguistic sciences, and has provided the topic for a chain of experimental and computational psycholinguistics papers. Baker’s crucial grammaticality facts, though much repeated in the literature, have not been critically investigated. A corpus investigation shows that his claims are not true: one does not take only phrasal antecedents, but can also take nouns on their own, including semantically relational nouns, and can take various of -PP dependents of its own. We give a semantic analysis of anaphoric one that allows it to exhibit this kind of freedom, and we exhibit frequency evidence that goes a long way toward explaining why linguists have been inclined to regard phrases like the one of physics or three ones as ungrammatical when in fact (as corpus evidence shows) they are merely dispreferred relative to available grammatical alternatives. The main implication for the acquisition literature is that one of the most celebrated arguments from poverty of the stimulus is shown to be without force.*

Prepositions in Applications: A Survey and Introduction to the Special Issue

Prepositions1—as well as prepositional phrases (PPs) and markers of various sorts— have a mixed history in computational linguistics (CL), as well as related fields such as artificial intelligence, information retrieval (IR), and computational psycholinguistics: On the one hand they have been championed as being vital to precise language understanding (e.g., in information extraction), and on the other they have been ignored on the grounds of being syntactically promiscuous and semantically vacuous, and relegated to the ignominious rank of “stop word” (e.g., in text classification and IR). Although NLP in general has benefitted from advances in those areas where prepositions have received attention, there are still many issues to be addressed. For example, in machine translation, generating a preposition (or “case marker” in languages such as Japanese) incorrectly in the target language can lead to critical semantic divergences over the source language string. Equivalently in information retrieval and information extraction, it would seem desirable to be able to predict that book on NLP and book about NLPmean largely the same thing, but paranoid about drugs and paranoid on drugs suggest very different things. Prepositions are often among the most frequent words in a language. For example, based on the British National Corpus (BNC; Burnard 2000), four out of the top-ten most-frequent words in English are prepositions (of, to, in, and for). In terms of both parsing and generation, therefore, accurate models of preposition usage are essential to avoid repeatedly making errors. Despite their frequency, however, they are notoriously difficult to master, even for humans (Chodorow, Tetreault, and Han 2007). For example, Lindstromberg (2001) estimates that less than 10% of upper-level English as a Second

Computational psycholinguistics: An interdisciplinary approach to the study of language By Matthew W. Crocker (review)

164LANGUAGE, VOLUME 74, NUMBER 1 (1998) (13) The Early Irish diphthongs conventionally spelled (ia) and (Ua) were /ia/ and /ua/, respectively , not /i:a/ and /u:a/. (Passim) The impression a specialist gets after reading this volume is that it would have benefited greatly from careful editing and proofreading. The volume as it presently exists will leave the linguist unfamiliar with the Celtic languages confused and all too frequently misinformed. (A lengthy list of references (306-35) gives the reader access to sounder secondary literature, but this is hardly a saving grace.) A second edition should be edited much more carefully, perhaps in consultation with specialists in the individual languages, and the descriptive presentation, especially in matters of syntax, should be less dense and more user-friendly. For now, the nonspecialist wishing to learn about the Celtic languages would be well advised to turn to the collected volumes mentioned infra. Indeed, perhaps a volume intending to treat the Celtic languages both diachronically and synchronically, both descriptively and theoretically (in parts), and with considerable attention to dialectal and sociolinguistic features, really ought to be prepared by a group rather than an individual. REFERENCES Ball, Martin J. (ed.) 1993. The Celtic languages. London: Routledge. MacAulay, Donald (ed.) 1992. The Celtic languages. Cambridge: Cambridge University Press. McCone, Kim (ed.) 1997. Compendium linguarum Celticarum. Wiesbaden: Dr. Ludwig Reichert Verlag, in preparation. Department of English Virginia Polytechnic Institute and State University Blacksburg, VA 24061-0112 [eska@vtaix.cc.vt.edu] Computational psycholinguistics: An interdisciplinary approach to the study of language . By Matthew W. Crocker. (Studies in theoretical psycholinguistics, 20.) Dordrecht: Kluwer, 1996. Pp. xii, 246. Reviewed by Dominique Estival, University of Melbourne Comparison with another book by the same title which came out at the same time (Dijkstra & de Smedt, 1996) shows that the new field of computational psycholinguistics is as diverse as are both linguistics and psycholinguistics. Crocker follows very faithfully the main tenets of the Chomskyan approach to syntax, and his book presents an implementation of the principles and parameters (P&P) framework, while D&S (a collection of 15 papers by researchers in psycholinguistics , linguistics, and AI) presents a completely opposite approach to language processing, namely the use of connectionist networks. The main limitation of Cs work however, is not the framework it adopts but the fact that while D&S covers both language comprehension and language production, C does not attempt to treat language processing but is limited both to the sentence level and toperception. Nevertheless , within those limitations, C argues very persuasively for the adequacy of the model he has chosen to the task he has undertaken. C attempts to demonstrate that the model of competence underlying the P&P approach to grammar can also serve as the basis for the implementation of a model of performance. He argues strongly: (1) for modularity (by which he really means autonomy of syntax); (2) against an interaction- or constraint-based model; (3) for a strongly principle-based parser (defined in Ch. 1, see below); and (4) against conflating competence and performance. These are central issues to be debated when designing a psychologically valid computational model of language processing, but his answers will not necessarily convince researchers in other lines of work. In particular, while I am sympathetic to Cs views on points 3 and 4, points 1 and 2 must largely be taken on faith, and his arguments have failed to persuade me. REVIEWS165 One problem with this book is that C assumes familiarity with the GB and P&P syntactic formalisms (for instance, the S node of the first figures becomes an IP node without explanation on p. 42), and although Ch. 3 later provides some introduction to the main concepts of the theory, the first two chapters should not presuppose such knowledge on the part of the reader if the audience is intended to be wider than syntacticians or psycholinguists working in this framework. While several approaches to processing are discussed, other syntactic theories are largely ignored. There is some comparison with LFG (in particular between Cs thematic structure and F-structure), but it is mainly dismissive, and there is no mention of either GPSG or HPSG, although the feature-based X-bar theory presented in Ch. 3 clearly owes a large...

Formal Issues in Lexical-Functional Grammar

Preface Part I. Formal Architecture: 1. The formal architecture of Lexical Functional Grammar Ronald M. Kaplan 2. Lexical Functional Grammar: a formal system for grammatical representation Ronald M. Kaplan and Joan Bresnan Part II. Nonlocal Dependencies: 3. Long-distance dependencies, constituent structure, and functional uncertainty Ronald M. Kaplan and Annie Zaenen 4. Modeling syntactic constrants on anaphoric binding Mary Dalrymple, John T. Maxwell III, and Annie Zaenen 5. An algorithm for functional uncertainty Ronald M. Kaplan and John T. Maxwell III 6. Constituent coordination in lexical functional grammar Ronald M. Kaplan and John T. Maxwell III Part III. Word Order: 7. Formal devices for linguisic generalizations: West Germanic world order in lexical functional grammar Annie Zaenen and Ronald M. Kaplan 8. Linear order, syntactic rank, and empty categories: on weak crossover Joan Bresnan Part IV. Semantics and Translation: 9. Projections and semantic description in lexical-functional grammar Per-Kristian Halvorsen and Ronald M. Kaplan 10. Situation semantics and semantic interpretation in constraint-based grammars Per-Kristian Halvorsen 11. Translation by structural correspondences Ronald M. Kaplan, Klaus Netter, Jurgen Wedekind and Annie Zaenen Part V. Mathematical and Computational Issues: 12. Three seductions of computational psycholinguistics Ronald M. Kaplan 13. Logic and feature structures Mark Johnson 14. A method for disjunctive constraint satisfaction John T. Maxwell III and Ronald M. Kaplan 15. The interface between phrasal and functional constraints John T. Maxwell III and Ronald M. Kaplan.

COMPUTATIONAL PSYCHOLINGUISTICS: AI AND CONNECTIONIST MODELS OF HUMAN LANGUAGE PROCESSING. Ton Dijkstra & Koenraad de Smedt (Eds.). Bristol, PA: Taylor & Francis, 1996. Pp. xv + 437. $79.95 cloth, $29.95 paper.

Computational Psycholinguistics is an integrated collection by researchers within psycholinguistics aimed at providing a balanced treatment of current computational modeling in both language perception and generation. The initial chapters of the book provide an introduction to the general techniques used in computational modeling (Dijkstra & de Smedt), as well as perspectives from traditional symbolic artificial intelligence (Daelemans & de Smedt) and connectionist approaches (Murre & Goebel). The themes presented in the introductory chapters are well integrated into the rest of the book, consistent with the goal of providing a relatively self-contained introduction, suitable for a graduate-level psycholinguistics classroom or a general introductory source.

Linguistic context analysis: a new approach to communication evaluation

Argues that not only quantitative, but also qualitative evaluation has become a necessity today to legitimize the effectiveness and efficiency of integrated communication activities to CEOs. The integration of computational psycholinguistics can improve corporate communication, and thus becomes a new strategic tool. An electronic dictionary has been created of basic, negative connotations for press releases and other communication tasks, which can be updated with client‐specific words. The focus on negative messages has the objective of detecting who, why and how publics are criticized, to learn from the vocabulary of opinion leaders and to improve issues management proactively. Suggests a new form of analysis called “computational linguistic context analysis” (CLCA) by analysing nominal groups of negative words, rather than monitoring content analysis in the traditional way.