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ZENODO
Dataset . 2021
Data sources: Datacite
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ZENODO
Dataset . 2021
Data sources: ZENODO
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ZENODO
Dataset . 2021
Data sources: Datacite
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JPS-daprinfo: A Dataset for Japanese Dialog Act Analysis and People-related Information Detection

Authors: Changzeng Fu; Chaoran Liu; Ishi, Carlos Toshinori; Ishiguro, Hiroshi;

JPS-daprinfo: A Dataset for Japanese Dialog Act Analysis and People-related Information Detection

Abstract

We conducted a labeling work on a spoken Japanese dataset (I-JAS) for the text classification, which contains 50 interview dialogues of two-way Japanese conversation that discuss the participants' past present and future. Each dialogue is 30 minutes long. From this dataset, we selected the interview dialogues of native Japanese speakers as the samples. Given the dataset, we annotated sentences with 13 labels. The labeling work was conducted by native Japanese speakers who have experience with data annotation. labels: ssi/osi:subjective information soi/ooi:objective information op/sp:plan qu:question ap:apology th:thanking cc:topic changing/closing ag:agreement ds:disagreement re:request pr:proposal su:summarize/reformulate th:other

Keywords

dialogue act, text classification

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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).
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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.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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