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American Sign Language Alphabet Recognition by Extracting Feature from Hand Pose Estimation
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In: Sensors ; Volume 21 ; Issue 17 (2021)
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| 2 |
Machine Learning Approach to Personality Type Prediction Based on the Myers–Briggs Type Indicator®
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In: Multimodal Technologies and Interaction ; Volume 4 ; Issue 1 (2020)
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La potenciación descortés del desacuerdo en hablantes españoles e ingleses ; Impolite boosting of disagreement in Spanish and English speakers
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Interactional Metadiscourse In Doctoral Thesis Writing: A Study in Kenya
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In: Applied Linguistics Research Journal, Vol 4, Iss 4, Pp 100-113 (2020) (2020)
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| 5 |
Computing Happiness from Textual Data
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In: Stats ; Volume 2 ; Issue 3 ; Pages 25-370 (2019)
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Abstract:
In this paper, we use a corpus of about 100,000 happy moments written by people of different genders, marital statuses, parenthood statuses, and ages to explore the following questions: Are there differences between men and women, married and unmarried individuals, parents and non-parents, and people of different age groups in terms of their causes of happiness and how they express happiness? Can gender, marital status, parenthood status and/or age be predicted from textual data expressing happiness? The first question is tackled in two steps: first, we transform the happy moments into a set of topics, lemmas, part of speech sequences, and dependency relations ; then, we use each set as predictors in multi-variable binary and multinomial logistic regressions to rank these predictors in terms of their influence on each outcome variable (gender, marital status, parenthood status and age). For the prediction task, we use character, lexical, grammatical, semantic, and syntactic features in a machine learning document classification approach. The classification algorithms used include logistic regression, gradient boosting, and fastText. Our results show that textual data expressing moments of happiness can be quite beneficial in understanding the &ldquo ; causes of happiness&rdquo ; for different social groups, and that social characteristics like gender, marital status, parenthood status, and, to some extent age, can be successfully predicted form such textual data. This research aims to bring together elements from philosophy and psychology to be examined by computational corpus linguistics methods in a way that promotes the use of Natural Language Processing for the Humanities.
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Keyword:
fastText; gradient boosting; happiness; lemmatization; lexical analysis; logistic regression; parsing; topic modeling
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URL: https://doi.org/10.3390/stats2030025
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| 6 |
Arabic-SOS: Segmentation, stemming, and orthography standardization for classical and pre-modern standard Arabic
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| 7 |
Computing Happiness from Textual Data
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In: 2 ; 3 ; 347 ; 370 (2019)
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| 9 |
IRISA at DeFT2017 : classification systems of increasing complexity ; Participation de l'IRISA à DeFT2017 : systèmes de classification de complexité croissante
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In: DeFT 2017 - Défi Fouille de texte ; https://hal.archives-ouvertes.fr/hal-01643993 ; DeFT 2017 - Défi Fouille de texte, Jun 2017, Orléans, France. pp.1-10 (2017)
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| 10 |
The Functions of Narrative Passages in Three Written Online Health Contexts
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In: Open Linguistics, Vol 2, Iss 1 (2016) (2016)
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| 11 |
ОБЗОР МЕТОДОВ И АЛГОРИТМОВ РАЗРЕШЕНИЯ ЛЕКСИЧЕСКОЙ МНОГОЗНАЧНОСТИ: ВВЕДЕНИЕ
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| 12 |
IRISA at DeFT 2015: Supervised and Unsupervised Methods in Sentiment Analysis
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In: DeFT, Défi Fouille de Texte, joint à la conférence TALN 2015 ; https://hal.archives-ouvertes.fr/hal-01226528 ; DeFT, Défi Fouille de Texte, joint à la conférence TALN 2015, Jun 2015, Caen, France (2015)
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| 13 |
A nonparametric Bayesian perspective for machine learning in partially-observed settings ...
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| 14 |
A nonparametric Bayesian perspective for machine learning in partially-observed settings
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| 15 |
All cumulative semantic interference is not equal: A test of the Dark Side Model of lexical access
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| 16 |
Sign Language Recognition using Sub-Units
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In: http://personal.ee.surrey.ac.uk/Personal/R.Bowden/publications/2012/Cooper_JMLR_2012.pdf (2012)
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| 17 |
Boosting of fuzzy rules with low quality data
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In: http://sci2s.ugr.es/publications/ficheros/JMVLSC2011.pdf (2011)
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| 18 |
Adasum: an adaptive model for summarization
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In: http://www.cs.fiu.edu/%7Elli003/Sum/CIKM/2008/p901-zhang.pdf (2008)
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| 19 |
A Multilingual Named Entity Recognition System Using Boosting and C4.5 Decision Tree Learning Algorithms. Discovery Science 2006
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In: http://www.inf.u-szeged.hu/~rfarkas/ds_lnai.pdf (2006)
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| 20 |
The ICSI+ Multilingual Sentence Segmentation System
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In: DTIC (2006)
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