The rapid development of the internet has resulted in rapid e-business growth, with online malls attracting many shoppers due to the privacy and convenience they offer. Like traditional malls, online malls can provide photos, specifications, prices, etc. However, consumers cannot touch the products in reality, which creates risks for the purchase. To date, there has been no research focusing on topic-specific search engines for 3C product reviews based on the trustworthiness of the reviews. This study is the first to sort the reviews of electronic products according to the degree of trust, by analyzing the characteristics of the reviews and the reviewers. This study proposes the criteria for features of the reviews and reviewers to consider to evaluate the trustworthiness of the reviews; builds a search engine to collect the product reviews scattered in opinion websites; and sorts the results by trustworthiness to provide a reliable e-commerce experience. To demonstrate the effectiveness of the proposed method, we conducted a set of experiments, and we adopted the Spearman’s rank correlation coefficient to evaluate the similarity between our method and experts’ opinions. The experimental results showed a high correlation coefficient with the opinions of experts, demonstrating that our method is effective at finding trustworthy reviews on the internet.