[Purpose/significance] The paper proposes an identification method based on the analysis of citations content. And a visual display is presented to overcome the problem of different citation emotions based on simple reference frequency measurement. [Method/process] First, it uses regular expressions to extract the content information of the text in full text. Then, it uses the TF-IDF algorithm to select the quoted emotion feature words, combines the emotional dictionary, and uses emotional analysis technology to quote emotion recognition. Finally, the use of visual tools shows the overall distribution of the reference emotion. [Result/conclusion] The method can effectively identify emotional information in the domain of anti-aging. The experimental results show that the positive citation accounts for 21% of the total citation frequency, neutral citation accounts for 78% of the total citation frequency, and negative citation accounts for only 1% of the total citation frequency. Compared with the traditional citation network, the visualization map based on citation emotion can effectively identify the distribution of different citation emotions on the overall data set.
Liao Junhua
,
Liu Ziqiang
,
Bai Rujiang
,
Chen Junying
. Citation Sentiment Recognition Method Based on Citation Content Analysis[J]. Library and Information Service, 2018
, 62(15)
: 112
-121
.
DOI: 10.13266/j.issn.0252-3116.2018.15.013
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