Visualizing multiple word similarity measures

Kievit-Kylar, Brent; Jones, Michael N.

doi:10.3758/s13428-012-0236-7

Cited by 11 publications

(9 citation statements)

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“…This raises the question of typical characteristics for models which happens to be a controversial issue in spite of the important analysis of models for instance by Jacobs and Grainger (1994) within the special area of visual word recognition. We would like to argue that models should be simple, exact, similar (to what is modeled), and fruitful (allowing predictions).…”

Section: Different Paradigms Instead Of a Taxonomy Of Functions: Consmentioning

confidence: 99%

Complementarity As Generative Principle: A Thought Pattern for Aesthetic Appreciations and Cognitive Appraisals in General

et al. 2017

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In experimental aesthetics the relationship between the arts and cognitive neuroscience has gained particular interest in recent years. But has cognitive neuroscience indeed something to offer when studying the arts? Here we present a theoretical frame within which the concept of complementarity as a generative or creative principle is proposed; neurocognitive processes are characterized by the duality of complementary activities like bottom-up and top-down control, or logistical functions like temporal control and content functions like perceptions in the neural machinery. On that basis a thought pattern is suggested for aesthetic appreciations and cognitive appraisals in general. This thought pattern is deeply rooted in the history of philosophy and art theory since antiquity; and complementarity also characterizes neural operations as basis for cognitive processes. We then discuss some challenges one is confronted with in experimental aesthetics; in our opinion, one serious problem is the lack of a taxonomy of functions in psychology and neuroscience which is generally accepted. This deficit makes it next to impossible to develop acceptable models which are similar to what has to be modeled. Another problem is the severe language bias in this field of research as knowledge gained in many languages over the ages remains inaccessible to most scientists. Thus, an inspection of research results or theoretical concepts is necessarily too narrow. In spite of these limitations we provide a selective summary of some results and viewpoints with a focus on visual art and its appreciation. It is described how questions of art and aesthetic appreciations using behavioral methods and in particular brain-imaging techniques are analyzed and evaluated focusing on such issues like the representation of artwork or affective experiences. Finally, we emphasize complementarity as a generative principle on a practical level when artists and scientists work directly together which can lead to new insights and broader perspectives on both sides.

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Section: Different Paradigms Instead Of a Taxonomy Of Functions: Consmentioning

confidence: 99%

Complementarity As Generative Principle: A Thought Pattern for Aesthetic Appreciations and Cognitive Appraisals in General

et al. 2017

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“…In particular, we explore the semantic spaces generated from American presidential debates during the period 1999-2016, and model how key political concepts are organized in different political parties and in individual presidential candidates (referred to below as Bpolitical semantic spaces^). Abstract political concepts have been previously shown to reflect party affiliations in semantic space models: using the BEAGLE model (Jones & Mewhort, 2007) on a set of 80 words from the State of the Union addresses by Presidents Bush and Obama, Kievit-Kylar and Jones (2012) showed that the concepts of economy and education are much more connected in Obama's speeches, whereas the concepts of war and terrorism had stronger connections in Bush's speeches. Moreover, the same concepts (e.g., security) were differentially connected to different terms (e.g., to military security in Bush's speeches vs. job security in Obama's speeches).…”

Section: Computational Modeling Of Individual Beliefs and Attitudesmentioning

confidence: 99%

Speaking two “Languages” in America: A semantic space analysis of how presidential candidates and their supporters represent abstract political concepts differently

Schloss

Follmer

2017

Behav Res

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In this article we report a computational semantic analysis of the presidential candidates' speeches in the two major political parties in the USA. In Study One, we modeled the political semantic spaces as a function of party, candidate, and time of election, and findings revealed patterns of differences in the semantic representation of key political concepts and the changing landscapes in which the presidential candidates align or misalign with their parties in terms of the representation and organization of politically central concepts. Our models further showed that the 2016 US presidential nominees had distinct conceptual representations from those of previous election years, and these patterns did not necessarily align with their respective political parties' average representation of the key political concepts. In Study Two, structural equation modeling demonstrated that reported political engagement among voters differentially predicted reported likelihoods of voting for Clinton versus Trump in the 2016 presidential election. Study Three indicated that Republicans and Democrats showed distinct, systematic word association patterns for the same concepts/terms, which could be reliably distinguished using machine learning methods. These studies suggest that given an individual's political beliefs, we can make reliable predictions about how they understand words, and given how an individual understands those same words, we can also predict an individual's political beliefs. Our study provides a bridge between semantic space models and abstract representations of political concepts on the one hand, and the representations of political concepts and citizens' voting behavior on the other.

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“…First descriptive models have taken up this challenge only recently, e.g., the NCPM (Jacobs, 2011, 2015a, 2016b) or Burke’s (2011) model of reading novels, but the way to formal computational models has yet to be paved by further research sufficiently constraining theory development (for a review of model types, see Jacobs and Grainger, 1994 or Hofmann and Jacobs, 2014). Note that even EADs to simple verbal materials such as single words still have not been modeled computationally, despite a wealth of formal models in the field of decision theory and neuroeconomics (e.g., Rangel and Clithero, 2014).…”

Section: Decision Tree (Recursive Partitioning) Modeling Of Eads To Smentioning

confidence: 99%

On Elementary Affective Decisions: To Like Or Not to Like, That Is the Question

2016

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Perhaps the most ubiquitous and basic affective decision of daily life is deciding whether we like or dislike something/somebody, or, in terms of psychological emotion theories, whether the object/subject has positive or negative valence. Indeed, people constantly make such liking decisions within a glimpse and, importantly, often without expecting any obvious benefit or knowing the exact reasons for their judgment. In this paper, we review research on such elementary affective decisions (EADs) that entail no direct overt reward with a special focus on Neurocognitive Poetics and discuss methods and models for investigating the neuronal and cognitive-affective bases of EADs to verbal materials with differing degrees of complexity. In line with evolutionary and appraisal theories of (aesthetic) emotions and data from recent neurocognitive studies, the results of a decision tree modeling approach simulating EADs to single words suggest that a main driving force behind EADs is the extent to which such high-dimensional stimuli are associated with the “basic” emotions joy/happiness and disgust.

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Visualizing multiple word similarity measures

Cited by 11 publications

References 50 publications

Complementarity As Generative Principle: A Thought Pattern for Aesthetic Appreciations and Cognitive Appraisals in General

Complementarity As Generative Principle: A Thought Pattern for Aesthetic Appreciations and Cognitive Appraisals in General

Speaking two “Languages” in America: A semantic space analysis of how presidential candidates and their supporters represent abstract political concepts differently

On Elementary Affective Decisions: To Like Or Not to Like, That Is the Question

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