Research on stock similarity and community division based on user attention sequence

Research on stock similarity and community division based on user attention sequence

We conduct research from the perspective of user groups and analyze the differences in the users' attention and posting order in different time periods to vectorize stocks and build relationships from the generatedx vectors. This provides a new perspective for the complex network cconstruction...

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Bibliographic Details
Main Authors: Zhang Gaowei, Xu Lingyu, Wang Lei
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201818910022
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spelling doaj-bbd3be14be3d4e40ba3fb0828ac000472021-02-02T00:48:48ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-011891002210.1051/matecconf/201818910022matecconf_meamt2018_10022Research on stock similarity and community division based on user attention sequenceZhang GaoweiXu LingyuWang LeiWe conduct research from the perspective of user groups and analyze the differences in the users' attention and posting order in different time periods to vectorize stocks and build relationships from the generatedx vectors. This provides a new perspective for the complex network cconstruction and community division of network public opinion space. The experiment result show that we can get the community division consistent with reality using our model.https://doi.org/10.1051/matecconf/201818910022
collection DOAJ
language English
format Article
sources DOAJ
author Zhang Gaowei
Xu Lingyu
Wang Lei
spellingShingle Zhang Gaowei
Xu Lingyu
Wang Lei
Research on stock similarity and community division based on user attention sequence
MATEC Web of Conferences
author_facet Zhang Gaowei
Xu Lingyu
Wang Lei
author_sort Zhang Gaowei
title Research on stock similarity and community division based on user attention sequence
title_short Research on stock similarity and community division based on user attention sequence
title_full Research on stock similarity and community division based on user attention sequence
title_fullStr Research on stock similarity and community division based on user attention sequence
title_full_unstemmed Research on stock similarity and community division based on user attention sequence
title_sort research on stock similarity and community division based on user attention sequence
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2018-01-01
description We conduct research from the perspective of user groups and analyze the differences in the users' attention and posting order in different time periods to vectorize stocks and build relationships from the generatedx vectors. This provides a new perspective for the complex network cconstruction and community division of network public opinion space. The experiment result show that we can get the community division consistent with reality using our model.
url https://doi.org/10.1051/matecconf/201818910022
work_keys_str_mv AT zhanggaowei researchonstocksimilarityandcommunitydivisionbasedonuserattentionsequence
AT xulingyu researchonstocksimilarityandcommunitydivisionbasedonuserattentionsequence
AT wanglei researchonstocksimilarityandcommunitydivisionbasedonuserattentionsequence
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