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.
Manuchehr Naderi Varandi; Vida Shaghaghi; Pantea Foroudi; Shahla Raghibdoust; Mohamadtaghi Taghavifard
Abstract
AbstractThe purpose of this study is to find out the role of textual paralinguistic features with an emphasis on letter repetition in social media and the possibility of using these features in advertising and social media marketing. Finding the role of letter repetition with a paralinguistic function ...
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AbstractThe purpose of this study is to find out the role of textual paralinguistic features with an emphasis on letter repetition in social media and the possibility of using these features in advertising and social media marketing. Finding the role of letter repetition with a paralinguistic function can help companies select the most repeated letters in words chosen especially for devising brand names and the most effective sentences henceforth regarding the appropriate contexts. Context has been emphasized for showing the gender, age, and feelings of language users from a sociolinguistic aspect and has taken special attention in interactional sociolinguistics in recent years. The role of letter repetition as a paralinguistic element in advertising contexts with a focus on the effect of this factor on the audience in social media discourse has not been studied in the Persian language. For this purpose, in order to find the frequency of the most repeated letters in Persian language social media discourse, Instagram and Telegram were selected for data mining and the five most repeated letters were identified and selected for further study through three research focusing on the following variables: 1. The use of letter repetition as a paralinguistic factor in social media 2. The use of letter repetition in advertising brand names in social media 3. The pronounceability of brand names and sentential advertisements in social media regarding the paralinguistic use of the five most repeated letters in the written discourse of the Persian language social media. The design of the study was mixed and the research was applied and descriptive of a content analysis type. The population was both male and female subjects with an age range of ten to eighty. In doing the research, both qualitative and quantitative data were used and some phases were followed. First, the primary data were gathered in social media by data-mining through web crawling in Python software. The software was applied to mine the most frequent letters in the Persian language used in written social media discourse and the number of their repetitions. The results of this part were used for designing questionnaires in the second phase of the research. The purpose of the first phase was to find the pattern in the use of letters applied by Iranians in social media. For the validation of the data during this phase, a questionnaire was devised and distributed among the students at the universities in Tehran and their families. In this way, the hypothesis regarding the most repeated letters and their use in social media proposed in the first research question was tested. Moreover, the pronounceability quality of the words with repeated letters was also studied and the use of letters in words in case of being beautifully pronounceable at sentential level was verified for use in advertising and brand names. In the second phase, two questionnaires were devised and distributed among 1508 people in order to assess the relationship of the use of the paralinguistic feature of letter repetition with brand names and the design of sentences in advertisements for marketing purposes. Twenty sentences with some words containing repeated letters were designed to test the pronounceability variable in the questionnaires. Cronbach’s alpha coefficient was used to determine the reliability of the questionnaires and to determine the face and content validity, the corrective comments of experts were applied. The results of the first and second phases of research showed that the highly frequent letters of alif [ɑ] (not the glottal stop), v, y, kh [x] and r are advised to be used for devising brand names regarding the pronounceability factor for marketing purposes. The findings of this research can be used for social media marketing, devising brand names, and advertising written sentences. The use of emojis, punctuation marks, esoteric marks, and other textual features is proposed for future research. The cultural perspective of consumers is a factor that cannot be ignored and the use of paralinguistic elements in different societies and cultures can be of special importance in this regard. Due to the importance of neurology in discourse studies, good research topics can be proposed for finding the role of letter repetition and other paralinguistic features in marketing from a neurolinguistic window, too.Keywords: Textual Paralanguage, Letter Repetition, Social Media, Marketing, Brand Names, Crawling.
sajad farhadi; Mohamadtaghi Taghavifard
Abstract
The present study is intended to answer the question that how the quality of life in dialysis patients can be monitored by mobile-health-based information technology. This was an applied-developmental study, in which the indices introduced in the Kidney Disease Quality of Life Short Form (KDQOL-SF) were ...
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The present study is intended to answer the question that how the quality of life in dialysis patients can be monitored by mobile-health-based information technology. This was an applied-developmental study, in which the indices introduced in the Kidney Disease Quality of Life Short Form (KDQOL-SF) were initially ranked from the viewpoints of three groups of physicians, patients and their hospital attendants, and the weighting criteria of each indicator were specified. In the following, the dynamic system for monitoring quality of life in dialysis patients was modeled and designed based on the weight of the obtained indices. The architecture provided for the system is based on three-layer MVC architectural pattern. The reporting services and access levels were also used in the design of the system. The results of ranking of the main indices of the quality of life in chronic kidney patients suggest that although the opinions of the groups of physicians and hospital attendants are different in weighting the criteria, they are similar in ranking of indices. Moreover, accurate analysis and collecting the data obtained from the ranking of quality indices were used in the implementation of the system to form the data model; and after the analysis and modification, a suitable model for system requirements was designed and used.
