Mobile Application for Customers’ Reviews Opinion Mining

Přichystal, Jan

doi:10.1016/j.sbspro.2016.05.511

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…Collecting, storing, retrieving and displaying reviews are difficult because of their large numbers. Moreover, the structure of the review data (which generally involves either unstructured or semi-structured formats) is complex, making the data Consumer purchasing behaviour difficult to analyse and process using traditional quantitative analysis (Larsen et al, 2008;P richystal, 2016;Khan and Vorley, 2017). Usually, online reviews are analysed to understand people's opinions, attitudes and emotions using information retrieval technology, natural language processing technology and data mining technology (Xu, 2015).…”

Section: Online Review Miningmentioning

confidence: 99%

Using online reviews to explore consumer purchasing behaviour in different cultural settings

Zhong

Liang

Cui

et al. 2019

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Purpose The purpose of this paper is to analyse consumer purchasing behaviour in different cultural settings by exploring the value of consumer reviews from various countries. Design/methodology/approach This study uses online review mining technology to collect, process and analyse user review data from multiple countries. The main procedures of this research are data collection, data pre-processing, feature extraction and sentiment analysis. Online reviews from the American, British and Indian websites for the iPhone 5s are analysed. Findings Every country has unique cultural characteristics, and these cultural differences affect consumers’ perceptions, attitudes and purchasing behaviours. The results show that consumers from different countries exhibit different levels of attention towards the same product and have different emotional inclinations for the same product feature. In addition, the study also identified the advantages and disadvantages of the product. Limitations implications The user reviews provide abundant feedback information that serves as a good intelligence resource for companies. Under the premise of different language habits, this paper uses a universal approach to analyse consumer behaviour from online reviews in different countries, which can help reveal consumers’ emotional inclination towards each feature of a product. This approach can be extended to other brands of mobile phones or other industries. Practical implications Multinational companies should analyse the cultural characteristics of target groups when proposing transnational development strategies. Companies can understand the perceptions of their products based on the consumer reviews and can formulate their marketing and product strategies by considering consumer purchasing behaviours arising from cultural differences. Originality/value This study identifies differences in consumer behaviour in different cultural settings by using a data mining method, which can help companies understand consumer perceptions and the performance and quality of product features.

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Section: Online Review Miningmentioning

confidence: 99%

Using online reviews to explore consumer purchasing behaviour in different cultural settings

Zhong

Liang

Cui

et al. 2019

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“…Jan Prichystal [4] merancang dan membangun aplikasi untuk perangkat mobile yang berfungsi mengidentifikasikan perasaan seseorang yang direpresentasikan dalam pesan teks dari customer review. Customer biasanya mencari dan membaca review dari customer-customer lain yang telah membeli atau menggunakan produk yang dimaksud, sebelum memutuskan untuk membeli produk tersebut.…”

Section: Tinjauan Pustakaunclassified

“…Customer biasanya mencari dan membaca review dari customer-customer lain yang telah membeli atau menggunakan produk yang dimaksud, sebelum memutuskan untuk membeli produk tersebut. Penelitian [4] berfokus pada review negatif dan positif terhadap suatu produk, sehingga membantu user mengidentifikasikan bahwa produk tersebut menarik untuk dibeli. Opini yang diperoleh dari review customer terhadap produk diolah menjadi Word Clouds.…”

Section: Tinjauan Pustakaunclassified

“…Jika word cloud yang berukuran besar adalah positif, maka user akan akan menemukan opini yang positif, dan jika cloud word yang berukuran besar adalah negatif maka user akan menemukan opini yang negatif. Pendekatan yang digunakan [4] fokus terhadap perolehan hasil yang cepat, sehingga kurang akurat dalam menganalisis. Pendekatan [4] tidak mampu menentukan polaritas kata yang memiliki banyak makna atau ekspresi.…”

Section: Tinjauan Pustakaunclassified

“…Pendekatan yang digunakan [4] fokus terhadap perolehan hasil yang cepat, sehingga kurang akurat dalam menganalisis. Pendekatan [4] tidak mampu menentukan polaritas kata yang memiliki banyak makna atau ekspresi.…”

Section: Tinjauan Pustakaunclassified

See 2 more Smart Citations

Opinion Miningframework Berbasiskan Leksikal

Christina

2018

JTI

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Opinion Mining and Sentiment Analysis can contribute in improving system performance tomeet the user’s needs. The text that represents the user's opinion may express the emotions oropinions implicitly or explicitly. The words that compose the sentence of opinion can have manydifferent meanings, related to the subject being discussed or the words that compose the sentence.This study, conducted a literature study on several researches that related to opinion mining, anddesigned an opinion mining framework based lexicon.

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