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Research data . Dataset . 2019

Past Written Texts Dataset

Ellul, John; Polycarpou, Marina;
Open Access
Published: 07 May 2019
Publisher: Zenodo
Abstract

The dataset consists of features extracted from older adults’ text. The texts were written by the older person either in an electronic mean (eg. older e-mail), or in paper form and were transcribed by the project's clinical nurses. The texts were then translated to English using the MyMemory service (https://mymemory.translated.net/), and a series of features were generated that can be used for sentiment analysis. The list of fields of this dataset is presented below: - Part_id: The user ID, which should be a 4-digit number - Date: The recording date, which follows the “DD-MM-YY” format (eg. 14 September 2017, is formatted as 14-09-17) - Clinical_visit: As several clinical evaluations were performed to each older adult, this number shows for which clinical evaluation these measurements refer to - Transcript: If the text was written by the older adult (0) or was transcribed by a nurse (1) - Language: The original language of the text (0 = Greek) - Text_length, Number_of_sentences, Number_of_words, Number_of_words_per_sentence, Text_entropy: Statistical Measures - Desc_image_ENG_sentiment, Desc_event_sentiment, Prev_text_ENG_sentiment: Sentiment Analysis - Tf-XX: Term frequency – Inverse document frequency - Tf-pos-XX: Part of Speech analysis, using tf-idf methodology

Subjects

social media sensing, sentiment analysis, text-based sentiment analysis

Funded by
EC| FrailSafe
Project
FrailSafe
Sensing and predictive treatment of frailty and associated co-morbidities using advanced personalized patient models and advanced interventions
  • Funder: European Commission (EC)
  • Project Code: 690140
  • Funding stream: H2020 | RIA
,
EC| FrailSafe
Project
FrailSafe
Sensing and predictive treatment of frailty and associated co-morbidities using advanced personalized patient models and advanced interventions
  • Funder: European Commission (EC)
  • Project Code: 690140
  • Funding stream: H2020 | RIA
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