Business Sentiment Quotient Analysis using Natural Language Processing

التفاصيل البيبلوغرافية
العنوان:	Business Sentiment Quotient Analysis using Natural Language Processing
المؤلفون:	Syed Salim, Madhu B K
المساهمون:	Blue Eyes Intelligence Engineering & Sciences Publication(BEIESP)
المصدر:	International Journal of Engineering and Advanced Technology (IJEAT) 9(4) 1350-1352
سنة النشر:	2020
المجموعة:	Zenodo
مصطلحات موضوعية:	Word2vec, Business Sentiment Quotient, Natural Language Processing, ISSN, Retrieval Number
الوصف:	Online business has opened up several avenues for researchers and computer scientists to initiate new research models. The business activities that the customers accomplish certainly produce abundant information /data. Analysis of the data/information will obviously produce useful inferences and many declarations. These inferences may support the system in improving the quality of service, understand the current market requirement, Trend of the business, future need of the society and so on. In this connection the current paper is trying to propose a feature extraction technique named as Business Sentiment Quotient (BSQ). BSQ involves word2vec[1] word embedding technique from Natural Language Processing. Number of tweets related to business are accessed from twitter and processed to estimate BSQ using python programming language. BSQ may be utilized for further Machine Learning Activities.
نوع الوثيقة:	article in journal/newspaper
اللغة:	English
تدمد:	2249-8958
العلاقة:	https://zenodo.org/record/5558610Test; https://doi.org/10.35940/ijeat.D8721.049420Test; oai:zenodo.org:5558610
DOI:	10.35940/ijeat.D8721.049420
الإتاحة:	https://doi.org/10.35940/ijeat.D8721.049420Test https://zenodo.org/record/5558610Test
حقوق:	info:eu-repo/semantics/openAccess ; https://creativecommons.org/licenses/by/4.0/legalcodeTest
رقم الانضمام:	edsbas.6283546D
قاعدة البيانات:	BASE

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الوصف
تدمد:	22498958
DOI:	10.35940/ijeat.D8721.049420