scholarly journals Linguistic positivity in historical texts reflects dynamic environmental and psychological factors

2016 ◽  
Vol 113 (49) ◽  
pp. E7871-E7879 ◽  
Author(s):  
Rumen Iliev ◽  
Joe Hoover ◽  
Morteza Dehghani ◽  
Robert Axelrod
Keyword(s):  
New York ◽  
American English ◽  
New York Times ◽  
Essential Dimension ◽  
Cognitive Mechanisms ◽  
Societal Factors ◽  
Historical Texts ◽  
Text Corpora ◽  
Google Books ◽  
Scientific Questions

People use more positive words than negative words. Referred to as “linguistic positivity bias” (LPB), this effect has been found across cultures and languages, prompting the conclusion that it is a panhuman tendency. However, although multiple competing explanations of LPB have been proposed, there is still no consensus on what mechanism(s) generate LPB or even on whether it is driven primarily by universal cognitive features or by environmental factors. In this work we propose that LPB has remained unresolved because previous research has neglected an essential dimension of language: time. In four studies conducted with two independent, time-stamped text corpora (Google books Ngrams and the New York Times), we found that LPB in American English has decreased during the last two centuries. We also observed dynamic fluctuations in LPB that were predicted by changes in objective environment, i.e., war and economic hardships, and by changes in national subjective happiness. In addition to providing evidence that LPB is a dynamic phenomenon, these results suggest that cognitive mechanisms alone cannot account for the observed dynamic fluctuations in LPB. At the least, LPB likely arises from multiple interacting mechanisms involving subjective, objective, and societal factors. In addition to having theoretical significance, our results demonstrate the value of newly available data sources in addressing long-standing scientific questions.

scholarly journals Interpretable Topic Extraction and Word Embedding Learning Using Non-Negative Tensor DEDICOM

2021 ◽  
Vol 3 (1) ◽  
pp. 123-167
Author(s):  
Lars Hillebrand ◽  
David Biesner ◽  
Christian Bauckhage ◽  
Rafet Sifa
Keyword(s):  
New York ◽  
Matrix Factorization ◽  
New York Times ◽  
Extraction Methods ◽  
Word Embedding ◽  
Topic Extraction ◽  
Text Understanding ◽  
Text Corpora ◽  
Embedding Performance ◽  
Information Matrices

Unsupervised topic extraction is a vital step in automatically extracting concise contentual information from large text corpora. Existing topic extraction methods lack the capability of linking relations between these topics which would further help text understanding. Therefore we propose utilizing the Decomposition into Directional Components (DEDICOM) algorithm which provides a uniquely interpretable matrix factorization for symmetric and asymmetric square matrices and tensors. We constrain DEDICOM to row-stochasticity and non-negativity in order to factorize pointwise mutual information matrices and tensors of text corpora. We identify latent topic clusters and their relations within the vocabulary and simultaneously learn interpretable word embeddings. Further, we introduce multiple methods based on alternating gradient descent to efficiently train constrained DEDICOM algorithms. We evaluate the qualitative topic modeling and word embedding performance of our proposed methods on several datasets, including a novel New York Times news dataset, and demonstrate how the DEDICOM algorithm provides deeper text analysis than competing matrix factorization approaches.

Inhaltsanalyse elektronisch gespeicherter Massendaten der internationalen Presse

2003 ◽  
Vol 15 (3) ◽  
pp. 98-105 ◽  
Author(s):  
Mark Galliker ◽  
Jan Herman
Keyword(s):  
New York ◽  
New York Times

Zusammenfassung. Am Beispiel der Repräsentation von Mann und Frau in der Times und in der New York Times wird ein inhaltsanalytisches Verfahren vorgestellt, das sich besonders für die Untersuchung elektronisch gespeicherter Printmedien eignet. Unter Co-Occurrence-Analyse wird die systematische Untersuchung verbaler Kombinationen pro Zähleinheit verstanden. Diskutiert wird das Problem der Auswahl der bei der Auswertung und Darstellung der Ergebnisse berücksichtigten semantischen Einheiten.

An historical analysis of species references in American English

Corpora ◽  
2019 ◽  
Vol 14 (3) ◽  
pp. 327-349
Author(s):  
Craig Frayne
Keyword(s):  
Environmental Change ◽  
Sentiment Analysis ◽  
Quantitative Methods ◽  
English Language ◽  
Language Use ◽  
American English ◽  
Historical Analysis ◽  
The Past ◽  
Corpus Studies ◽  
Google Books

This study uses the two largest available American English language corpora, Google Books and the Corpus of Historical American English (coha), to investigate relations between ecology and language. The paper introduces ecolinguistics as a promising theme for corpus research. While some previous ecolinguistic research has used corpus approaches, there is a case to be made for quantitative methods that draw on larger datasets. Building on other corpus studies that have made connections between language use and environmental change, this paper investigates whether linguistic references to other species have changed in the past two centuries and, if so, how. The methodology consists of two main parts: an examination of the frequency of common names of species followed by aspect-level sentiment analysis of concordance lines. Results point to both opportunities and challenges associated with applying corpus methods to ecolinguistc research.

The Portrayal of Islam and Muslims in Western Media: A Critical Discourse Analysis

Cultura ◽  
2019 ◽  
Vol 16 (1) ◽  
pp. 53-73
Author(s):  
Saman REZAEI ◽  
Kamyar KOBARI ◽  
Ali SALAMI
Keyword(s):  
New York ◽  
Discourse Analysis ◽  
Critical Discourse Analysis ◽  
New York Times ◽  
Critical Discourse ◽  
Cognitive Approach ◽  
Global Village ◽  
Online Newspapers ◽  
Terrorist Groups ◽  
Western Media

With the realization of the promised global village, media, particularly online newspapers, play a significant role in delivering news to the world. However, such means of news circulation can propagate different ideologies in line with the dominant power. This, coupled with the emergence of so-called Islamic terrorist groups, has turned the focus largely on Islam and Muslims. This study attempts to shed light on the image of Islam being portrayed in Western societies through a Critical Discourse Analysis approach. To this end, a number of headlines about Islam or Muslims have been randomly culled from three leading newspapers in Western print media namely The Guardian, The Independent and The New York Times (2015). This study utilizes “ideological square” notion of Van Dijk characterized by “positive presentation” of selves and “negative presentation” of others alongside his socio-cognitive approach. Moreover, this study will take the linguistic discourses introduced by Van Leeuwen regarding “representing social actors and social practices” into consideration. The findings can be employed to unravel the mystery behind the concept of “Islamophobia” in Western societies. Besides, it can reveal how specific lexical items, as well as grammatical structures are being employed by Western media to distort the notion of impartiality.

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