排名(信息检索)
社会化媒体
计算机科学
产品(数学)
客户情报
夸张
数据科学
客户保留
情报检索
营销
业务
万维网
服务质量
服务(商务)
心理学
精神科
数学
几何学
作者
Ramandeep Sandhu,Amritpal Singh,Mohammad Faiz,Harpreet Kaur,Sunny Thukral
标识
DOI:10.1002/9781119785491.ch3
摘要
Most customers say that online reviews influence their decisions to purchase a new product. Therefore, it is no exaggeration to say that online reviews are critical to the success of a business. A star rating only cannot lead to decision making for a customer; text reviews play a vital role in product recommendations. Collecting online reviews and transforming them into valuable insights is highly beneficial for both the customer and the company. This chapter proposes an enhanced text-mining approach based on social media data. The proposed technique works on real-time customer reviews in the form of tweets, calculates the frequency-based ranking and has provided promising results.
科研通智能强力驱动
Strongly Powered by AbleSci AI