Building sentiment lexicons based on recommending services for the Polish language

Gliwa, Bogdan; Zygmunt, Anna; Dąbrowski, Michał

doi:10.7494/csci.2016.17.2.163

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…The online information usually composes of opinions or feelings expressed by the Internet users about services, healthcare, products, politics, etc. Determining and understanding the Internet users' opinions (e.g., happy or unhappy) using sentiment analysis is the vital key-role to apply to marketing, and making decisions or recommendations [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

A new approach for extracting and scoring aspect using SentiWordNet

Tran

Duangsuwan

Wettayaprasit

2021

IJEECS

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Aspect-based online information on social media plays a vital role in influencing people’s opinions when consumers concern with their decisions to make a purchase, or companies intend to pursue opinions on their product or services. Determining aspect-based opinions from the online information is necessary for business intelligence to support users in reaching their objectives. In this study, we propose the new aspect extraction and scoring system which has three procedures. The first procedure is normalizing and tagging part-of-speech for sentences of datasets. The second procedure is extracting aspects with pattern rules. The third procedure is assigning scores for aspects with SentiWordNet. In the experiments, benchmark datasets of customer reviews are used for evaluation. The performance evaluation of our proposed system shows that our proposed system has high accuracy when compared to other systems.

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Section: Introductionmentioning

confidence: 99%

A new approach for extracting and scoring aspect using SentiWordNet

Tran

Duangsuwan

Wettayaprasit

2021

IJEECS

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show abstract

“…To get relevant information by retrieving and mining opinions from the huge volume is one of the tasks in opinion mining. Because of the beneficial effects on understanding customer opinions, opinion mining has been studied by researchers in many languages [1,8,12,21,22,25,29,32] and applied to sentiment-summarization systems [11,13,14,48]. These summarization systems can help people observe different perspectives from their summaries to make decisions.…”

Section: Introductionmentioning

confidence: 99%

A Novel Framework for Aspect Knowledgebase Generated Automatically from Social Media Using Pattern Rules

Tran

Duangsuwan

Wettayaprasit

2021

csci

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One of the factors improving businesses in business intelligence is summarization systems which could generate summaries based on sentiment from social media. However, these systems could not produce automatically, they used annotated datasets. To automatically produce sentiment summaries without using the annotated datasets, we propose a novel framework using pattern rules. The framework has two procedures: 1) pre-processing and 2) aspect knowledgebase generation. The first procedure is to check and correct misspelt words (bigram and unigram) by a proposed method, and tag part-of-speech all words. The second procedure is to automatically generate aspect knowledgebase used to produce sentiment summaries by the sentiment summarization systems. Pattern rules and semantic similarity-based pruning are used to automatically generate aspect knowledgebase from social media. In the experiments, eight domains from benchmark datasets of reviews are used. The performance evaluation of our proposed approach shows the high performance when compared to other approaches.

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