<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Bi B</submitter><funding>National Natural Science Foundation of China</funding><pagination>e0266598</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9004763</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>17(4)</volume><pubmed_abstract>Although social media has highly facilitated people's daily communication and dissemination of information, it has unfortunately been an ideal hotbed for the breeding and dissemination of Internet rumors. Therefore, automatically monitoring rumor dissemination in the early stage is of great practical significance. However, the existing detection methods fail to take full advantage of the semantics of the microblog information propagation graph. To address this shortcoming, this study models the information transmission network of a microblog as a heterogeneous graph with a variety of semantic information and then constructs a Microblog-HAN, which is a graph-based rumor detection model, to capture and aggregate the semantic information using attention layers. Specifically, after the initial</pubmed_abstract><journal>PloS one</journal><pubmed_title>Microblog-HAN: A micro-blog rumor detection model based on heterogeneous graph attention network.</pubmed_title><pmcid>PMC9004763</pmcid><funding_grant_id>72171005</funding_grant_id><pubmed_authors>Bi B</pubmed_authors><pubmed_authors>Zhang H</pubmed_authors><pubmed_authors>Gao Y</pubmed_authors><pubmed_authors>Wang Y</pubmed_authors></additional><is_claimable>false</is_claimable><name>Microblog-HAN: A micro-blog rumor detection model based on heterogeneous graph attention network.</name><description>Although social media has highly facilitated people's daily communication and dissemination of information, it has unfortunately been an ideal hotbed for the breeding and dissemination of Internet rumors. Therefore, automatically monitoring rumor dissemination in the early stage is of great practical significance. However, the existing detection methods fail to take full advantage of the semantics of the microblog information propagation graph. To address this shortcoming, this study models the information transmission network of a microblog as a heterogeneous graph with a variety of semantic information and then constructs a Microblog-HAN, which is a graph-based rumor detection model, to capture and aggregate the semantic information using attention layers. Specifically, after the initial</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022</publication><modification>2025-04-21T17:34:02.538Z</modification><creation>2025-04-21T17:34:02.538Z</creation></dates><accession>S-EPMC9004763</accession><cross_references><pubmed>35413070</pubmed><doi>10.1371/journal.pone.0266598</doi></cross_references></HashMap>