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ZENODO
Software . 2021
License: CC BY
Data sources: ZENODO
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ZENODO
Software . 2021
License: CC BY
Data sources: Datacite
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EDGAR-W2V Embeddings

Authors: Lefteris Loukas; Fergadiotis, Manos; Androutsopoulos, Ion; Prodromos Malakasiotis;

EDGAR-W2V Embeddings

Abstract

EDGAR-W2V: the word embeddings trained on EDGAR-CORPUS. EDGAR-W2V is 200-dimensional and contains a financial vocabulary of 100k tokens, which is also attached. EDGAR-W2V is found in the paper entitled "EDGAR-CORPUS: Billions of Tokens Make The World Go Round", Proceedings of the Workshop on Economics and Natural Language Processing (ECONLP) - co-located with EMNLP 2021

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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.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
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142
18