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2016-01-04
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2016-01-05
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2016-01-06
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2016-01-07
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2016-01-08
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2016-01-11
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2016-01-12
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2016-01-13
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2016-01-14
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2016-01-15
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2016-01-19
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2016-01-20
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2016-01-21
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2016-01-22
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2016-01-25
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2016-01-26
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2016-01-27
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2016-01-28
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2016-01-29
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2016-02-01
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2016-02-02
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2016-02-03
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2016-02-04
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2016-02-05
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2016-02-08
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2016-02-09
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2016-02-10
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2016-02-11
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2016-02-12
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2016-02-22
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2016-02-23
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2016-02-25
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2016-02-26
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2016-02-29
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2016-03-01
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2016-03-02
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2016-03-03
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2016-03-04
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2016-03-07
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2016-03-08
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2016-03-09
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2016-03-10
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2016-03-11
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2016-03-14
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2016-03-15
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2016-03-16
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2016-03-17
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2016-03-18
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2016-03-21
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2016-03-22
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2016-03-23
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2016-03-24
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2016-03-28
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2016-03-29
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2016-03-30
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2016-03-31
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2016-04-01
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2016-04-04
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2016-04-05
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2016-04-06
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2016-04-07
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2016-04-08
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2016-04-11
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2016-04-12
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2016-04-13
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2016-04-14
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2016-04-15
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2016-04-18
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2016-04-19
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2016-04-20
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2016-04-21
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2016-04-22
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2016-04-25
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2016-04-26
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2016-04-27
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2016-04-28
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2016-04-29
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2016-05-05
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2016-05-06
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2016-05-09
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2016-05-10
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2016-05-11
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2016-05-12
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2016-05-13
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2016-05-16
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2016-05-17
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2016-05-20
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2016-05-23
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2016-05-24
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2016-05-25
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AMZN

Dataset Card for Earnings Calls Dataset

Dataset Summary

The dataset reports a collection of earnings call transcripts, the related stock prices, and the sector index In terms of volume, there is a total of 188 transcripts, 11970 stock prices, and 1196 sector index values. Furthermore, all of these data originated in the period 2016-2020 and are related to the NASDAQ stock market. Furthermore, the data collection was made possible by Yahoo Finance and Thomson Reuters Eikon. Specifically, Yahoo Finance enabled the search for stock values and Thomson Reuters Eikon provided the earnings call transcripts. Lastly, the dataset can be used as a benchmark for the evaluation of several NLP techniques to understand their potential for financial applications. Moreover, it is also possible to expand the dataset by extending the period in which the data originated following a similar procedure.

Citation Information

@data{TJE0D0_2021,
author = {Roozen, Dexter and Lelli, Francesco},
publisher = {DataverseNL},
title = {{Stock Values and Earnings Call Transcripts: a Sentiment Analysis Dataset}},
year = {2021},
version = {V1},
doi = {10.34894/TJE0D0},
url = {https://doi.org/10.34894/TJE0D0}
}
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