In the last few years, the growth rate of the number of people who are active on Twitter has been consistently spiking. In India, even the government agencies have started using Twitter accounts as they feel that they can get connected to a greater number of people in a short span of time. Apart from the social media platforms, there are an enormous number of blogging applications that have popped up providing another platform for the people to share their views. With all this, the authenticity of the content that is being generated is going for a toss. On that note, the authors have the task in hand of differentiating the genuineness of the content. In this process, they have worked upon various techniques that would maximize the authenticity of the content and propose a long short-term memory (LSTM) model that will make a distinction between the tweets posted on the Twitter platform. The model in combination with the manually engineered features and the bag of words model is able to classify the tweets efficiently.
{"title":"Classification of Tweets Into Facts and Opinions Using Recurrent Neural Networks","authors":"Murugan Pattusamy, Lakshmi Kanth","doi":"10.4018/ijthi.319358","DOIUrl":"https://doi.org/10.4018/ijthi.319358","url":null,"abstract":"In the last few years, the growth rate of the number of people who are active on Twitter has been consistently spiking. In India, even the government agencies have started using Twitter accounts as they feel that they can get connected to a greater number of people in a short span of time. Apart from the social media platforms, there are an enormous number of blogging applications that have popped up providing another platform for the people to share their views. With all this, the authenticity of the content that is being generated is going for a toss. On that note, the authors have the task in hand of differentiating the genuineness of the content. In this process, they have worked upon various techniques that would maximize the authenticity of the content and propose a long short-term memory (LSTM) model that will make a distinction between the tweets posted on the Twitter platform. The model in combination with the manually engineered features and the bag of words model is able to classify the tweets efficiently.","PeriodicalId":44533,"journal":{"name":"International Journal of Technology and Human Interaction","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43590785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mahendar Goli, A. Sahu, Surajit Bag, Pavitra Dhamija
This research examines the effects of factors such as perceived ease of use, perceived usefulness, perceived enjoyment, innovativeness, perceived information quality, and perceived customisation on behavioural intention to use Chatbots. The research model designed is empirically validated using structural equation modelling with the aid of AMOS software. A five-point Likert scale-based structured questionnaire was used to collect data from 378 Chatbot users in an online method. The results indicated that the perceived ease of use, perceived usefulness, innovativeness, perceived information quality, and perceived customisation have positive effects on intention to use Chatbots, whereas perceived enjoyment is found to exert no effect. The research further discussed implications and future directions of research.
{"title":"Users' Acceptance of Artificial Intelligence-Based Chatbots","authors":"Mahendar Goli, A. Sahu, Surajit Bag, Pavitra Dhamija","doi":"10.4018/ijthi.318481","DOIUrl":"https://doi.org/10.4018/ijthi.318481","url":null,"abstract":"This research examines the effects of factors such as perceived ease of use, perceived usefulness, perceived enjoyment, innovativeness, perceived information quality, and perceived customisation on behavioural intention to use Chatbots. The research model designed is empirically validated using structural equation modelling with the aid of AMOS software. A five-point Likert scale-based structured questionnaire was used to collect data from 378 Chatbot users in an online method. The results indicated that the perceived ease of use, perceived usefulness, innovativeness, perceived information quality, and perceived customisation have positive effects on intention to use Chatbots, whereas perceived enjoyment is found to exert no effect. The research further discussed implications and future directions of research.","PeriodicalId":44533,"journal":{"name":"International Journal of Technology and Human Interaction","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42160429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Technology is a standard tool that first responders use in their assessment and planning during disasters. Despite the considerable number of hardware and software solutions adopted, first responders still often rely on paper plans when examining indoor disasters. The purpose of this research is to investigate the technical competencies of firefighters and test the building situation tool (BUST) to replace the paper plans. A mixed method approach was used to assess the technology self-efficacy and gather insight into perceived usefulness, ease of use, and the user experience from the firefighters (N=20). The findings show a sufficient level of competency, and that first time users prefer guided instructions, clarity in the user interface, controls, and options to customize the user interface. The findings have practical implications for the future development of BUST and its adoption to the workflow of firefighters.
{"title":"Assessment of the Building Situation Tool Adoption Among Firefighters","authors":"F. Sever","doi":"10.4018/ijthi.317749","DOIUrl":"https://doi.org/10.4018/ijthi.317749","url":null,"abstract":"Technology is a standard tool that first responders use in their assessment and planning during disasters. Despite the considerable number of hardware and software solutions adopted, first responders still often rely on paper plans when examining indoor disasters. The purpose of this research is to investigate the technical competencies of firefighters and test the building situation tool (BUST) to replace the paper plans. A mixed method approach was used to assess the technology self-efficacy and gather insight into perceived usefulness, ease of use, and the user experience from the firefighters (N=20). The findings show a sufficient level of competency, and that first time users prefer guided instructions, clarity in the user interface, controls, and options to customize the user interface. The findings have practical implications for the future development of BUST and its adoption to the workflow of firefighters.","PeriodicalId":44533,"journal":{"name":"International Journal of Technology and Human Interaction","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48505976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this paper is to identify factors predicting perceived intention of using IoT by Indians. To fulfill the purpose, basing on literature review and on diffusion theory of planned behavior (DTPB) model, factors predicting perceived intention of using IoT by the Indian consumers have been identified and hypotheses have been developed which were tested by collecting data using questionnaire from 400 concerned respondents. The data were analyzed and tested using different standard tools. The study revealed that: perceived usefulness, perceived ease of use, compatibility impact attitude, influence of family members, influence of peers, influence of others impact subjective norms, self-efficacy, and facilitating conditions impact perceived behavioral control. Again, attitude and perceived behavioral control influence intention though subjective norms significantly do not influence intention. Again, it is found that intention positively influences the actual use of IoT by the consumers. The outcome would help the IoT service providers to improve their businesses.
{"title":"Why Do People Use IoT-Enabled Devices?","authors":"Sheshadri Chatterjee","doi":"10.4018/ijthi.313626","DOIUrl":"https://doi.org/10.4018/ijthi.313626","url":null,"abstract":"The purpose of this paper is to identify factors predicting perceived intention of using IoT by Indians. To fulfill the purpose, basing on literature review and on diffusion theory of planned behavior (DTPB) model, factors predicting perceived intention of using IoT by the Indian consumers have been identified and hypotheses have been developed which were tested by collecting data using questionnaire from 400 concerned respondents. The data were analyzed and tested using different standard tools. The study revealed that: perceived usefulness, perceived ease of use, compatibility impact attitude, influence of family members, influence of peers, influence of others impact subjective norms, self-efficacy, and facilitating conditions impact perceived behavioral control. Again, attitude and perceived behavioral control influence intention though subjective norms significantly do not influence intention. Again, it is found that intention positively influences the actual use of IoT by the consumers. The outcome would help the IoT service providers to improve their businesses.","PeriodicalId":44533,"journal":{"name":"International Journal of Technology and Human Interaction","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46353505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The study aims to evaluate perceived impediments and anticipated solutions to HR while implementing Industry 4.0 initiatives in SMEs. A group of 10 decision-makers from these SMEs was tasked with assigning ratings to a variety of parameters. To create the model for 10 perceived impediments and five anticipated solutions and subsequently rank them, the TOPSIS technique is employed. According to the data analysis, job reductions, unemployment, and job uncertainty have emerged as the top three significant hurdles, while challenges to trainers, replacement of humans, and training costs have been recognized as the bottom three. Smart HR 4.0 and AI & Data Analytics are the top and lowest-ranked solutions respectively. HR in I4.0 in SMEs parameters have been graded based on their contributing attributes. However, it is also true that there are several impediments associated with the implementation of Industry 4.0. These impediments become more challenging in the context of SMEs.
{"title":"Perceived Impediments and Anticipated Solutions to HR (Human Resource) Towards Implementing Industry 4.0 in SMEs","authors":"N. Sharma, Vimal Kumar, K. Lai, Wen-Kuo Chen","doi":"10.4018/ijthi.306230","DOIUrl":"https://doi.org/10.4018/ijthi.306230","url":null,"abstract":"The study aims to evaluate perceived impediments and anticipated solutions to HR while implementing Industry 4.0 initiatives in SMEs. A group of 10 decision-makers from these SMEs was tasked with assigning ratings to a variety of parameters. To create the model for 10 perceived impediments and five anticipated solutions and subsequently rank them, the TOPSIS technique is employed. According to the data analysis, job reductions, unemployment, and job uncertainty have emerged as the top three significant hurdles, while challenges to trainers, replacement of humans, and training costs have been recognized as the bottom three. Smart HR 4.0 and AI & Data Analytics are the top and lowest-ranked solutions respectively. HR in I4.0 in SMEs parameters have been graded based on their contributing attributes. However, it is also true that there are several impediments associated with the implementation of Industry 4.0. These impediments become more challenging in the context of SMEs.","PeriodicalId":44533,"journal":{"name":"International Journal of Technology and Human Interaction","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41779111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study identifies coping strategies to examine the behaviors adopted by team managers in addressing technostress. It evaluates the choice of coping strategies to increase performance. A study involving 3 companies and 45 respondents was conducted to identify coping strategies. However, as we chose to make a deeper interview after the first one, we continued our interviews with those who are available for 8 hours of interview, (2 hours each time); therefore we continued with 13 people. Overall, four interactional coping strategies were identified: Based on these, four new coping theories address technostress from an international perspective. This enriches the literature on coping strategies and technostress and the results explain a wide range of team managers' behaviors. Hence, it is necessary to adopt suitable policies to address effect of technostress.
{"title":"Strategies to Respond to Technology Enhancement","authors":"Min Feng, Driss Bourazzouq","doi":"10.4018/ijthi.313624","DOIUrl":"https://doi.org/10.4018/ijthi.313624","url":null,"abstract":"This study identifies coping strategies to examine the behaviors adopted by team managers in addressing technostress. It evaluates the choice of coping strategies to increase performance. A study involving 3 companies and 45 respondents was conducted to identify coping strategies. However, as we chose to make a deeper interview after the first one, we continued our interviews with those who are available for 8 hours of interview, (2 hours each time); therefore we continued with 13 people. Overall, four interactional coping strategies were identified: Based on these, four new coping theories address technostress from an international perspective. This enriches the literature on coping strategies and technostress and the results explain a wide range of team managers' behaviors. Hence, it is necessary to adopt suitable policies to address effect of technostress.","PeriodicalId":44533,"journal":{"name":"International Journal of Technology and Human Interaction","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43302692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Employers' feedback on new college graduates' performance is a crucial piece of information that schools must consider to identify the relevance and responsiveness of their curriculum, programs, and services. Hence, in this paper, the artificial intelligence assisted satisfaction index model (AI-SIM) has been proposed to identify the college students' job satisfaction. Computer systems with advanced artificial intelligence can engage in reasoning, sensing, and responding in the most dynamic and complex environments. Artificial intelligence systems are being adopted rapidly by organizations to manage their workforce. This article aims to present the research results where contract the assessment made by graduates of the training at the University with necessary professional competences in the labour market. Job satisfaction toward colleague has the highest mean, meanwhile opportunities for promotion are the lowest. The implication of college student volunteer's systems and practices are discussed.
{"title":"Construction and Empirical Analysis of College Students' Job Satisfaction Index Model Using Artificial Intelligence","authors":"Lingchong Jia","doi":"10.4018/ijthi.313603","DOIUrl":"https://doi.org/10.4018/ijthi.313603","url":null,"abstract":"Employers' feedback on new college graduates' performance is a crucial piece of information that schools must consider to identify the relevance and responsiveness of their curriculum, programs, and services. Hence, in this paper, the artificial intelligence assisted satisfaction index model (AI-SIM) has been proposed to identify the college students' job satisfaction. Computer systems with advanced artificial intelligence can engage in reasoning, sensing, and responding in the most dynamic and complex environments. Artificial intelligence systems are being adopted rapidly by organizations to manage their workforce. This article aims to present the research results where contract the assessment made by graduates of the training at the University with necessary professional competences in the labour market. Job satisfaction toward colleague has the highest mean, meanwhile opportunities for promotion are the lowest. The implication of college student volunteer's systems and practices are discussed.","PeriodicalId":44533,"journal":{"name":"International Journal of Technology and Human Interaction","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45279973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Social media sites employ various approaches to track feelings, including diagnosing neurological problems, including fear, in people or assessing a population public sentiment. One essential obstacle for automatic emotion recognition principles is variable with fluctuating limitations, language, and interpretation shifts. Therefore, in this paper, a deep learning-based emotion recognition (DL-EM) system has been proposed to describe the various relational effects in emotional groups. A soft classification method is suggested to quantify the tendency and allocate a message to each emotional class. A supervised framework for emotions in text streaming messages is developed and tested. Two of the major activities are offline teaching assignments and interactive emotion classification techniques. The first challenge offers templates in text responses to describe sentiment. The second activity includes implementing a two-stage framework to identify live broadcasts of text messages for dedicated emotion monitoring.
{"title":"Deep Learning Approach for Emotion Recognition Analysis in Text Streams","authors":"Chang Liu, S. Kirubakaran, Alfred Daniel J.","doi":"10.4018/ijthi.313927","DOIUrl":"https://doi.org/10.4018/ijthi.313927","url":null,"abstract":"Social media sites employ various approaches to track feelings, including diagnosing neurological problems, including fear, in people or assessing a population public sentiment. One essential obstacle for automatic emotion recognition principles is variable with fluctuating limitations, language, and interpretation shifts. Therefore, in this paper, a deep learning-based emotion recognition (DL-EM) system has been proposed to describe the various relational effects in emotional groups. A soft classification method is suggested to quantify the tendency and allocate a message to each emotional class. A supervised framework for emotions in text streaming messages is developed and tested. Two of the major activities are offline teaching assignments and interactive emotion classification techniques. The first challenge offers templates in text responses to describe sentiment. The second activity includes implementing a two-stage framework to identify live broadcasts of text messages for dedicated emotion monitoring.","PeriodicalId":44533,"journal":{"name":"International Journal of Technology and Human Interaction","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41529129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The empirical evaluation of the success of a participant is critical for a thorough assessment of sporting events. Evaluating students' efficiency or scripting in sports is limited, even if skilled experts do it. In this paper, support vector machine-assisted sports training (SVMST) has been proposed to evaluate student sports efficiency. Sports training prototypes are based on different criteria that participate in the matches, traditional game statistics, person quality measures, and opposing data. The success of students is divided into two grades: moderate and large. The primarily supervised learning-based classification method is used to create a template for identifying student sports training efficiency. SVM implements learning methods, data collection methods, effective model assessment methods, and particular difficulties in predicting sports performance. The experimental results show SVMST to high student performance of 98.7%, a low error rate of 9.8%, enhanced assessment ratio of 97.6%, training outcome of 95.6%, and an efficiency ratio of 96.8%.
{"title":"Evaluating the Efficiency of Student Sports Training Based on Supervised Learning","authors":"Song Kewei, Vicente García Díaz, Seifedine Kadry","doi":"10.4018/ijthi.313427","DOIUrl":"https://doi.org/10.4018/ijthi.313427","url":null,"abstract":"The empirical evaluation of the success of a participant is critical for a thorough assessment of sporting events. Evaluating students' efficiency or scripting in sports is limited, even if skilled experts do it. In this paper, support vector machine-assisted sports training (SVMST) has been proposed to evaluate student sports efficiency. Sports training prototypes are based on different criteria that participate in the matches, traditional game statistics, person quality measures, and opposing data. The success of students is divided into two grades: moderate and large. The primarily supervised learning-based classification method is used to create a template for identifying student sports training efficiency. SVM implements learning methods, data collection methods, effective model assessment methods, and particular difficulties in predicting sports performance. The experimental results show SVMST to high student performance of 98.7%, a low error rate of 9.8%, enhanced assessment ratio of 97.6%, training outcome of 95.6%, and an efficiency ratio of 96.8%.","PeriodicalId":44533,"journal":{"name":"International Journal of Technology and Human Interaction","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47149469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The present study aimed to investigate the mediating role of smartphone addiction in the association between vulnerability and relationship satisfaction among younger adults living in Turkey. The relationship assessment scale, the smartphone addiction scale-short version, the psychological vulnerability scale, and the social vulnerability scale were applied to 326 university students. Structural equation modelling showed that vulnerability has a significantly direct effect on relationship satisfaction, and smartphone addiction can partially mediate the impact of vulnerability on relationship satisfaction. The bootstrapping techniques confirmed that smartphone addiction had a partial mediation effect between vulnerability and relationship satisfaction. These data may help clinicians and researchers to better understand the consequences of vulnerability and underlying the processes of smartphone addiction and relationship satisfaction.
{"title":"Vulnerability and Relationship Satisfaction","authors":"B. Satici","doi":"10.4018/ijthi.313625","DOIUrl":"https://doi.org/10.4018/ijthi.313625","url":null,"abstract":"The present study aimed to investigate the mediating role of smartphone addiction in the association between vulnerability and relationship satisfaction among younger adults living in Turkey. The relationship assessment scale, the smartphone addiction scale-short version, the psychological vulnerability scale, and the social vulnerability scale were applied to 326 university students. Structural equation modelling showed that vulnerability has a significantly direct effect on relationship satisfaction, and smartphone addiction can partially mediate the impact of vulnerability on relationship satisfaction. The bootstrapping techniques confirmed that smartphone addiction had a partial mediation effect between vulnerability and relationship satisfaction. These data may help clinicians and researchers to better understand the consequences of vulnerability and underlying the processes of smartphone addiction and relationship satisfaction.","PeriodicalId":44533,"journal":{"name":"International Journal of Technology and Human Interaction","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43954099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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