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基于DSLML的雞蛋消費(fèi)在線評(píng)論情感分析
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現(xiàn)代農(nóng)業(yè)產(chǎn)業(yè)技術(shù)體系北京市家禽創(chuàng)新團(tuán)隊(duì)建設(shè)項(xiàng)目(2021)


Sentimental Analysis of Online Reviews of Egg Consumption Based on DSLML
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    隨著信息技術(shù),、包裝和物流技術(shù)的快速發(fā)展,,包括農(nóng)產(chǎn)品在內(nèi)的電商產(chǎn)品范圍和規(guī)模越來越大,同時(shí),,網(wǎng)上購(gòu)物在線評(píng)論數(shù)據(jù)也呈指數(shù)級(jí)增加,。在線評(píng)論成為關(guān)注的熱點(diǎn)。以京東電商平臺(tái)為例,,挖掘雞蛋消費(fèi)在線評(píng)論文本,,深入分析消費(fèi)者雞蛋消費(fèi)情感傾向,提出了一種結(jié)合機(jī)器學(xué)習(xí)的領(lǐng)域情感詞典(Domain sentimental lexicon with machine learning,,DSLML)分類方法,,該方法通過情感傾向逐點(diǎn)互信息(Semantic orientation pointwise mutual information,,SO-PMI)方法構(gòu)建領(lǐng)域情感詞典,并選擇機(jī)器學(xué)習(xí)模型作為情感分類器,,實(shí)現(xiàn)對(duì)雞蛋在線評(píng)論的情感傾向分類,;然后構(gòu)建LDA主題模型挖掘出雞蛋評(píng)論中的正、負(fù)向主題,。實(shí)驗(yàn)結(jié)果表明,,與單獨(dú)的機(jī)器學(xué)習(xí)模型和領(lǐng)域情感詞典(Domain sentimental lexicon,,DSL)相比,,DSLML分類模型在文本情感傾向分類中的各指標(biāo)均有所提升;主題挖掘結(jié)果表明,,消費(fèi)者最為關(guān)心的是雞蛋品質(zhì)和包裝,。本研究結(jié)論可以為雞蛋電商經(jīng)營(yíng)者有針對(duì)性提升經(jīng)營(yíng)策略、提高服務(wù)質(zhì)量提供數(shù)據(jù)支持和理論支撐,。

    Abstract:

    With the rapid development of information technology, packaging and logistics technology, the range and scale of E-commerce products, including agricultural products, are getting larger and larger. At the same time, the online shopping review data has grown exponentially.The online reviews has become a hotspot. Taking JDs E-commerce platform as an example, the online reviews were mined out and the sentimental tendency of consumers about eggs consumption was analyzed deeply. The main research contents included proposing a domain sentimental lexicon with machine learning (DSLML) classification method. The semantic orientation pointwise mutual information (SO-PMI) method was used to construct the domain sentimental lexicon, and then a machine learning model was selected as the classifier to achieve the classification of sentimental orientation of online egg reviews. Then the LDA topic model was constructed to mine out the positive and negative topics in egg reviews. The experimental results showed that the DSLML classification model was improved in each indicator of text sentimental tendency classification, compared with machine learning models and domain sentimental lexicon (DSL) alone. From the results of the theme mining, the quality of eggs and the packaging of goods were the two aspects that consumers mostly concerned about. The conclusion of this research can provide data support and theoretical support for egg E-commerce operators to improve business strategies and service quality.

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包乾輝,李佳利,石淑珍,戴 引,劉 雪.基于DSLML的雞蛋消費(fèi)在線評(píng)論情感分析[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2021,52(S0):496-503. BAO Qianhui, LI Jiali, SHI Shuzhen, DAI Yin, LIU Xue. Sentimental Analysis of Online Reviews of Egg Consumption Based on DSLML[J]. Transactions of the Chinese Society for Agricultural Machinery,2021,52(S0):496-503.

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  • 收稿日期:2021-07-16
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  • 在線發(fā)布日期: 2021-11-10
  • 出版日期: 2021-12-10
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