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Natural Language Processing for Computing the Influence of Language on Perception and Behavior.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Natural Language Processing for Computing the Influence of Language on Perception and Behavior./
作者:	Pryzant, Reid.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	135 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-05, Section: B.
Contained By:	Dissertations Abstracts International83-05B.
標題:	Language. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28688363
ISBN:	9798544204480

Natural Language Processing for Computing the Influence of Language on Perception and Behavior.
Pryzant, Reid.

Natural Language Processing for Computing the Influence of Language on Perception and Behavior. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 135 p.

Source: Dissertations Abstracts International, Volume: 83-05, Section: B.

Thesis (Ph.D.)--Stanford University, 2021.

This item must not be sold to any third party vendors.

Modern natural langauge processing (NLP) systems have achieved outstanding improvements over the last ten years, due in part to the rise of highly expressive multi-layer neural networks and massive datasets. Despite this progress, however, large gaps remain between the language capabilities of NLP systems and human beings. First, these systems operate as engines of correlation which specialize heavily to the data on which they are trained and evaluated. Second, human understanding of language is embedded in social context, with abstract and non-literal cues like subjectivity and identity that are difficult to integrate with traditional supervised and unsupervised machine learning frameworks.This dissertation seeks to make two steps forward with respect to these limitations of correlational machine learning and abstract social understanding. Both steps involve building NLP systems with the ability to reason about language in terms of how readers might respond to that language. First, I propose algorithms for discovering which parts of a text are causally implicated in behavioral responses among readers, and for estimating the causal effect of linguistic properties on behavior. In the second step, I propose generative algorithms for automatically manipulating the presence of abstract social concepts in text. In particular, I focus on the case of subjective bias, developing a text editing system which is the fusion of a discriminative bias identification module and generative text editing module.Overall, this dissertation argues that despite recent breakthroughs in NLP, the limits of language technology remain behind that of human beings. It attempts to close this gap by developing systems which can reason in new ways about how readers respond to text.

ISBN: 9798544204480Subjects--Topical Terms:

643551
Language.

Natural Language Processing for Computing the Influence of Language on Perception and Behavior.
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