By a News Reporter-Staff News Editor at Life Science Weekly -- Data detailed on Life Science Research have been presented. According to news originating from Heilongjiang, People’s Republic of China, by NewsRx correspondents, research stated, “Analyzing massive user-generated microblogs is very crucial in many fields, attracting many researchers to study. However, it is very challenging to process such noisy and short microblogs.”
Funders for this research include National Natural Science Foundation of China, Research Fund for the Doctoral Program of Higher Education of China, The Youth Science Foundation of Heilongjiang Province of China, Heilongjiang postdoctoral Fund, China Scholarship Council.
Our news journalists obtained a quote from the research from Harbin Engineering University, “Most prior works only use texts to identify sentiment polarity and assume that microblogs are independent and identically distributed, which ignore microblogs are networked data. Therefore, their performance is not usually satisfactory. Inspired by two sociological theories (sentimental consistency and emotional contagion), in this paper, we propose a new method combining social context and topic context to analyze microblog sentiment. In particular, different from previous work using direct user relations, we introduce structure similarity context into social contexts and propose a method to measure structure similarity. In addition, we also introduce topic context to model the semantic relations between microblogs. Social context and topic context are combined by the Laplacian matrix of the graph built by these contexts and Laplacian regularization are added into the microblog sentiment analysis model.”
According to the news editors, the research concluded: “Experimental results on two real Twitter datasets demonstrate that our proposed model can outperform baseline methods consistently and significantly.”
For more information on this research see: Microblog sentiment analysis using social and topic context. Plos One , 2018;13(2):e0191163. (Public Library of Science - www.plos.org; Plos One - www.plosone.org)
The news correspondents report that additional information may be obtained from X. Zou, School of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang, People’s Republic of China. Additional authors for this research include J. Yang and J. Zhang.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1371/journal.pone.0191163. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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CITATION: (2018-02-20), Data on Life Science Research Reported by Researchers at Harbin Engineering University (Microblog sentiment analysis using social and topic context), Life Science Weekly, 1783, ISSN: 1552-2474, BUTTER® ID: 015170346
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