Kernels for Text Analysis

Analyzing Language in Suicide Notes and Legacy Tokens

Crisis ◽

10.1027/0227-5910/a000363 ◽

2016 ◽

Vol 37 (2) ◽

pp. 140-147 ◽

Cited By ~ 6

Author(s):

Michael J. Egnoto ◽

Darrin J. Griffin

Keyword(s):

Text Analysis ◽

Low Cost ◽

Computer Software ◽

Student Writing ◽

Computer Assisted ◽

Automated Identification ◽

Completed Suicide ◽

Suicide Notes ◽

Self Harm ◽

Harm To Others

Abstract. Background: Identifying precursors that will aid in the discovery of individuals who may harm themselves or others has long been a focus of scholarly research. Aim: This work set out to determine if it is possible to use the legacy tokens of active shooters and notes left from individuals who completed suicide to uncover signals that foreshadow their behavior. Method: A total of 25 suicide notes and 21 legacy tokens were compared with a sample of over 20,000 student writings for a preliminary computer-assisted text analysis to determine what differences can be coded with existing computer software to better identify students who may commit self-harm or harm to others. Results: The results support that text analysis techniques with the Linguistic Inquiry and Word Count (LIWC) tool are effective for identifying suicidal or homicidal writings as distinct from each other and from a variety of student writings in an automated fashion. Conclusion: Findings indicate support for automated identification of writings that were associated with harm to self, harm to others, and various other student writing products. This work begins to uncover the viability or larger scale, low cost methods of automatic detection for individuals suffering from harmful ideation.

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Using computerized text analysis to examine associations between linguistic features and clients’ distress during psychotherapy.

Journal of Counseling Psychology ◽

10.1037/cou0000440 ◽

2020 ◽

Cited By ~ 1

Author(s):

Natalie Shapira ◽

Gal Lazarus ◽

Yoav Goldberg ◽

Eva Gilboa-Schechtman ◽

Rivka Tuval-Mashiach ◽

...

Keyword(s):

Text Analysis ◽

Linguistic Features ◽

Computerized Text Analysis

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Couple Experiences of Intimate Partner Violence: A Network Text Analysis of Conversations

PsycEXTRA Dataset ◽

10.1037/e579192012-147 ◽

2012 ◽

Author(s):

Erica Hartwell

Keyword(s):

Intimate Partner Violence ◽

Text Analysis ◽

Partner Violence ◽

Intimate Partner ◽

Network Text Analysis

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DARR: A Free-text Analysis System for the Automatic Documentation of Radiological Reports

Methods of Information in Medicine ◽

10.1055/s-0038-1636585 ◽

1977 ◽

Vol 16 (03) ◽

pp. 144-153 ◽

Cited By ~ 3

Author(s):

E. Vaccari ◽

W. Delaney ◽

A. Chiesa

Keyword(s):

Natural Language ◽

Text Analysis ◽

Automatic Documentation ◽

Free Text ◽

Software System ◽

Automatic Translation ◽

Radiological Report ◽

Analysis System ◽

Content Processing

A software system for the automatic free-text analysis and retrieval of radiological reports is presented. Such software involves: (1) automatic translation of the specific natural language in a formalized metalanguage in order to transform the radiological report in a »normalized report« analyzable by computer; (2) content processing of the normalized report to select desired information. The approach used to accomplish point (1) is described in detail referring to a specific application.

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A Medical Text Analysis System for German - Syntax Analysis

Methods of Information in Medicine ◽

10.1055/s-0038-1634842 ◽

1991 ◽

Vol 30 (04) ◽

pp. 275-283 ◽

Cited By ~ 7

Author(s):

P. M. Pietrzyk

Keyword(s):

Text Analysis ◽

Free Text ◽

New Approach ◽

Syntax Analysis ◽

Medical Text ◽

Medical Language ◽

Computerized Processing ◽

Language Data ◽

Analysis System ◽

German Syntax

Abstract:Much information about patients is stored in free text. Hence, the computerized processing of medical language data has been a well-known goal of medical informatics resulting in different paradigms. In Gottingen, a Medical Text Analysis System for German (abbr. MediTAS) has been under development for some time, trying to combine and to extend these paradigms. This article concentrates on the automated syntax analysis of German medical utterances. The investigated text material consists of 8,790 distinct utterances extracted from the summary sections of about 18,400 cytopathological findings reports. The parsing is based upon a new approach called Left-Associative Grammar (LAG) developed by Hausser. By extending considerably the LAG approach, most of the grammatical constructions occurring in the text material could be covered.

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Factors of Price Formation for Art Objects With the Application of Text Analysis of Twitter News

Экономическая наука современной России ◽

10.33293/1609-1442-2020-2(89)-114-131 ◽

2020 ◽

pp. 114-131

Author(s):

Elena A. Fedorova ◽

Diana V. Zaripova ◽

Igor S. Demin

Keyword(s):

Text Analysis ◽

Price Formation ◽

Works Of Art ◽

Art Objects ◽

Online Resource ◽

The Difference

This work confirmed the hypotheses about the influence of the mood index on Twitter on the pricing of art objects and the difference between the experts' estimations and the final price of the auction. The hypotheses were tested with the use of a sample of 83 paintings selected on the basis of ratings of ARTNET's online resource about the most expensive works of art ever sold in the last 10–15 years. The sample consisted of 25 artists, for each of them was made an index of moods on Twitter. This index was created by a sentimental analysis of each tweet about the artist on the hashtag for a period of 2 to 4 months between the announcements of sales in the open sources and the direct sale of the work with the use of the two dictionaries AFINN and NRC.

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