印度尼西亚电子商务市场营销情报工作的情绪分析比较
A Comparison of Indonesia E-Commerce Sentiment Analysis for Marketing Intelligence Effort
摘要：
印度尼西亚电子商务市场的快速增长，使得各种电子商务公司出现，并且它们之间存在高度竞争。营销情报是衡量竞争地位的重要活动。营销情报的一个要素是评估客户满意度。许多印尼客户通过社交媒体表达对公司的满意或不满。因此，使用社交媒体数据提供了一种新的实用方法来衡量营销情报工作。本研究使用TF-IDF加权的朴素贝叶斯分类器分类方法进行情感分析。我们比较了前三大电子商务网站访问公司的情绪，分别是Bukalapak，Tokopedia和Elevenia。我们使用Twitter数据进行情绪分析，因为它更快，更便宜，从客户和研究人员方面都更容易。本研究的目的是找出如何处理庞大的客户情绪Twitter成为有用的信息，为电子商务公司，这些前3名的电子商务公司有最高的客户满意度。实验结果表明，该方法能够对社交媒体Twitter中的客户情绪进行自动分类，Elevenia是客户满意度最高的电子商务。
英文摘要：
The rapid growth of the e-commerce market in Indonesia, making various e-commerce companies appear and there has been high competition among them. Marketing intelligence is an important activity to measure competitive position. One element of marketing intelligence is to assess customer satisfaction. Many Indonesian customers express their sense of satisfaction or dissatisfaction towards the company through social media. Hence, using social media data provides a new practical way to measure marketing intelligence effort. This research performs sentiment analysis using the naive bayes classifier classification method with TF-IDF weighting. We compare the sentiments towards of top-3 e-commerce sites visited companies, are Bukalapak, Tokopedia, and Elevenia. We use Twitter data for sentiment analysis because it's faster, cheaper, and easier from both the customer and the researcher side. The purpose of this research is to find out how to process the huge customer sentiment Twitter to become useful information for the e-commerce company, and which of those top-3 e-commerce companies has the highest level of customer satisfaction. The experiment results show the method can be used to classify customer sentiments in social media Twitter automatically and Elevenia is the highest e-commerce with customer satisfaction.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
