基于大数据的在线零售业情感分析:大数据与在线零售商分类主动联动的概念定量研究

Muhammad Faisal Sultan, Mehwish Jabeen, Muhammad Adeel Mannan
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引用次数: 0

摘要

大数据是数据科学在全球范围内流行的最新趋势。该工具在知识优化方面具有显著的辅助作用,在知识和生产力的优化方面具有主导作用。然而,正如盖洛普巴基斯坦(2018)所指出的那样,对概念及其在巴基斯坦的应用缺乏理解,数据流将在两年后翻一番。因此,明确需要进行研究,以便从巴基斯坦的背景下优化对技术及其应用的理解。因此,考虑到大数据在零售领域的应用,本研究旨在通过大数据对在线商店有效分类的影响来探索情感分析的影响。虽然数据是通过配额抽样从与在线零售部门相关的IT专家那里收集的,但为了分析的目的,已经纳入了SMART-PLS。研究结果强调,大数据被认为是改善在线零售商店分类的主要工具,尽管数据科学家及其适用性可能会削弱大数据使用的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment Analysis through Big Data in online Retail Industry: A Conceptual Quantitative Study on linkage of Big-Data and Assortment Proactive of Online Retailers
Big-Data is the recent trend in data sciences prevailing all over the globe. The tool aids significantly in optimization of knowledge and has predominant use in optimization of knowledge and productivity. However, there is lack of understanding of concept and its application in Pakistan as indicated by Gallup Pakistan (2018) and stream of data is going to be doubled in two years’ time Tankard (2012). Therefore, there is a definite need of research which optimizes understanding associated with technology and its application from the context of Pakistan. Hence considering the application of big-data in retail sector this study aims to explore the impact of sentiment analysis through relating impact of big-data with effective assortment s of online stores. Although data has been collected from IT experts associated with online retail sector via quota sampling and SMART-PLS has been incorporated for the purpose of analysis. Results of the study highlights that big-data is perceived as the major tool for the betterment of assortment in online retail stores although data scientist and their applicability might diminish the impact of the use of big-data.
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