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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
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https://doi.org/10.5281/zenodo...
Dataset . 2019
License: CC BY
Data sources: Sygma
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Past Written Texts Dataset

Authors: Ellul, John; Polycarpou, Marina;

Past Written Texts Dataset

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

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Keywords

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

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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