[Purpose/significance] This study aims to identify events from the text of sudden network public opinion quickly and accurately.[Method/process] This paper proposed a method to identify network public opinion emergencies by integrating syntactic features and syntactic similarity. An event oriented syntactic feature extraction method was proposed based on syntactic features. Event syntactic feature database was constructed by using event semantic annotation and syntactic feature extraction methods. The network public opinion emergencies were identified by calculating the syntactic similarity between the text to be tested and the syntax database.[Result/conclusion] Taking the novel coronavirus pneumonia epidemic as an example, the optimal similarity of the network public opinion emergency identification method proposed by the author is 0.93 in this public opinion. 160 events and 30 non events are identified from a new text under this similarity, and the F1 value reaches 0.848. Through the method evaluation, it is proved that the proposed method is effective in using syntactic similarity to identify events and merge the same adjacent parts of speech.
Chen Jianyao
,
Zhai Shanshan
,
Xia Lixin
,
Liu Deyin
. Research on Network Public Opinion Emergency Recognition Method Based on Syntactic Features and Syntactic Similarity[J]. Library and Information Service, 2021
, 65(9)
: 41
-50
.
DOI: 10.13266/j.issn.0252-3116.2021.09.005
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