Kamran Farajzadeh; Mohamadtaghi Taghavifard; Abbas Toloie Ashlaghi; Alireza Rashidi Komayjan
Abstract
AbstractIntroduction:Today, many fields of research and business deal with the thoughts, images and mental patterns of their users and audiences. Knowing and being aware of the way of thinking of people, customers and audiences of a collection has a great impact on making appropriate decisions by the ...
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AbstractIntroduction:Today, many fields of research and business deal with the thoughts, images and mental patterns of their users and audiences. Knowing and being aware of the way of thinking of people, customers and audiences of a collection has a great impact on making appropriate decisions by the managers of that collection, in order to advance the goals and solve various problems. One of the important requirements of managers in any collection is to have sufficient knowledge of how they think about the collection and its performance. This helps them guide the group properly and make appropriate decisions in the way of advancing its goals. Therefore, collecting data from customers should be done with measured and accurate methods to achieve high quality information and obtain valid results. This research, by raising the question of "how can you use the analysis of people's feelings to find out how they think about a certain issue?", tries to provide a new approach on the platform of the Twitter social network to obtain reliable and high-quality information from people in relation to a certain topic. The purpose of the current research is to provide a new approach to collect data from people, in order to measure their perception about a specific issue. It will also examine the impact of the presented method on the speed, quality and cost of collecting data from people using a case study approach.Materials and Methods:In this research, their comments on the social network Twitter were used to check the satisfaction of users of three internet taxi applications in Iran, namely Snap, Tapsi, and Carpino. The data collection approach used in this research was descriptive, with results used by users, managers, and researchers. The research population consisted of all users of the three applications and members of the Twitter social network who had published their thoughts about these applications. The research collected and analyzed a total of 682 relevant tweets cross-sectionally during the summer of 1400 using the Twitter application interface and related hashtags. The analysis steps included data collection, pre-processing of tweets - including linguistic, sentiment, and thematic analysis, followed by sentiment analysis.Discussion and Results:The comparison of the analysis results from this research to the face-to-face interview method showed that the participation of respondents was challenging, and the traditional field method came with its own disadvantages. However, this method is able to overcome those issues and provide reliable results at a lower cost and time. Moreover, the results obtained from analyzing the data collected were similar to the results obtained through the face-to-face interview method, which speaks to the accuracy and quality of the data. Overall, the proposed method can provide valuable insights into people's thoughts and opinions on a particular topic, at a lower cost and time.Conclusions:The proposed method can be widely applicable to various fields, including business, research, and even everyday life. Managers, researchers, and business owners can use it to collect data and insights from their target audience, which can be analyzed to make informed decisions. Further development of the method can lead to even more useful and accurate reports, helping individuals and businesses stay ahead of their competitors. All students and researchers dealing with data collection can use this method to conduct their studies more effectively. Additionally, market research companies can use it to gain valuable feedback from consumers, informing their next steps in providing products and services.Overall, the applications of this research are far-reaching, and it provides a valuable resource for individuals and organizations looking to better understand their audience.Keywords: Sentiment analysis, text mining, how people think, Twitter, Internet taxi.
