Thus, product review analysis is a widely accepted platform where consumer can easily aware of their requirements. In this experiment, we track 568,454 fine food reviews of 74,258 products and 256,059 users on
Moreover, it is a well-established task in many business applications like movie reviews that can enhance or damage the revenue of the movie, and product reviews that can praise the quality of a product or damage the product sales. In the literature, sentiment analysis performed on either ...
Since reviews of much work on sentiment analysis have already been included in [26], in this section, we will only review some previous work, upon which our research is essentially based. Hu and Liu [27] summarized a list of positive words and a list of negative words, respectively, based...
Product reviewsSalesJoint sentiment-topic analysisJSTMediation analysisThis research examines the business impact of online reviews. It empirically investigates the influence of numerical and textual reviews on product sales performance. We use a Joint Sentiment-Topic model to extract the topics and ...
Bose R, Dey RK, Roy S, Sarddar D (2020) Sentiment analysis on online product reviews. In: Information and communication technology for sustainable development. Springer, pp 559–569 Buder J, Rabl L, Feiks M, Badermann M, Zurstiege G (2021) Does negatively toned language use on social ...
However, this can sometimes result in errors, as some words with a negative connotation can be used in a positive context like, “The print on the sweater is sick.”4. Intent-basedIntent-based sentiment analysis takes into account a text’s sentiment as well as the underlying purpose, goal...
Hybrid approaches combine rule-based and machine-learning techniques and usually result in more accurate sentiment analysis. For example, a brand could train an algorithm on a set of rules and customer reviews, updating the algorithm until it catches nuances specific to the brand or industry....
Sentiment Analysis Tools enable organizations to analyze all forms of text data to determine the overall sentiment, opinion, or emotional tone expressed by the users in their messages. These tools use technologies such as machine learning, natural language processing (NLP), text analysis, and biometr...
Section 2 reviews the related work. Section 3 defines two problems of sentiment analysis on online videos. Two sentiment analysis strategies using TSC are proposed in Section 4 and Section 5. Section 6 evaluates the performance of the model using a TSC dataset. We conclude our work in Section...
The following two approaches were followed for sentiment analysis on product reviews: Machine learning models used for classification were leveraged in this research and were trained to classify the sentiment of product reviews. Multiple models were used for this purpose, i.e., Random Forest, Naive...