List of Articles social media

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  1 - Criteria for evaluating the effectiveness of social media users - a framework based on social media exploration
  rojyar pirmohammadiani shahriyar mohammadi
  Nowadays, users' interactive behaviors on social media have become an important and influential resource on marketing activities in various businesses. Despite the importance of this issue, providing appropriate criteria for evaluating the influential behavior of user More

  Nowadays, users' interactive behaviors on social media have become an important and influential resource on marketing activities in various businesses. Despite the importance of this issue, providing appropriate criteria for evaluating the influential behavior of users in recent studies has received less attention. For this purpose, in the first step, an innovative theory framework including two main dimensions: potential of the influence and the level of the influence is presented. Then, in order to define criteria for measuring each dimension, by providing a comprehensive and combined classification including three domains, user-based analysis, relationship-based analysis and content-based analysis, exploration techniques Social media has been examined to analyze the effective behaviors of users. In the following, according to the literature review, the criteria of "number of active users", “ranked of users based on the structural indexes and activity", “quality and the subjectiveness of content” have been defined to measure each of the aforementioned dimensions. The criteria proposed in this article are effective for creating dashboards to assess the value of users' influence in various businesses. It also a comprehensive roadmap has been provided for businesses about the data they need to collect and the required techniques to determine each of these metrics through a cross-disciplinary and academic classification of social media exploration techniques. Manuscript profile
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  2 - Introducing a genetic algorithm based Method for Community person's stance Detection in social media and news
  mehdi salkhordeh haghighi Seyyed Mohammad  ebrahimi
  News reports in social media are presented with large volumes of different kinds of documents. The presented topics in these documents focus on different communities and person stances and opinions. Knowing the relationships among persons in the documents can help the r More

  News reports in social media are presented with large volumes of different kinds of documents. The presented topics in these documents focus on different communities and person stances and opinions. Knowing the relationships among persons in the documents can help the readers to obtain a basic knowledge about the subject and the purpose of various documents. In the present paper, we introduce a method for detecting communities that includes the persons with the same stances and ideas. To do this, the persons referenced in different documents are clustered into communities that have related positions and stances. In the presented method. Community-based personalities are identified based on a friendship network as a base method. Then by using a genetic algorithm, the way that these communities are identified is improved. The criterion in the tests is rand index of detection of these communities. The experiments are designed based on real databases that published in Google News on a particular topic. The results indicate the efficiency and desirability of the proposed method Manuscript profile
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  3 - A Hybrid Machine Learning Approach for Sentiment Analysis of Beauty Products Reviews
  Kanika Jindal Rajni Aron
  10.52547/jist.15586.10.37.1
  Nowadays, social media platforms have become a mirror that imitates opinions and feelings about any specific product or event. These product reviews are capable of enhancing communication among entrepreneurs and their customers. These reviews need to be extracted and an More

  Nowadays, social media platforms have become a mirror that imitates opinions and feelings about any specific product or event. These product reviews are capable of enhancing communication among entrepreneurs and their customers. These reviews need to be extracted and analyzed to predict the sentiment polarity, i.e., whether the review is positive or negative. This paper aims to predict the human sentiments expressed for beauty product reviews extracted from Amazon and improve the classification accuracy. The three phases instigated in our work are data pre-processing, feature extraction using the Bag-of-Words (BoW) method, and sentiment classification using Machine Learning (ML) techniques. A Global Optimization-based Neural Network (GONN) is proposed for the sentimental classification. Then an empirical study is conducted to analyze the performance of the proposed GONN and compare it with the other machine learning algorithms, such as Random Forest (RF), Naive Bayes (NB), and Support Vector Machine (SVM). We dig further to cross-validate these techniques by ten folds to evaluate the most accurate classifier. These models have also been investigated on the Precision-Recall (PR) curve to assess and test the best technique. Experimental results demonstrate that the proposed method is the most appropriate method to predict the classification accuracy for our defined dataset. Specifically, we exhibit that our work is adept at training the textual sentiment classifiers better, thereby enhancing the accuracy of sentiment prediction. Manuscript profile
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  4 - Evaluate the Effects of Service Innovation, Social Media Marketing, and Social Support on Value Co-creation
  akbar hoshyar Alireza Rousta
  The present research has evaluated the effects of service innovation, social media marketing and social support on value co-creation in Iran Khodro Company.This research is based on the achievement of the development-applicative type and based on the objectives of the d More

  The present research has evaluated the effects of service innovation, social media marketing and social support on value co-creation in Iran Khodro Company.This research is based on the achievement of the development-applicative type and based on the objectives of the descriptive type of the case that the necessary data has been collected by the survey method. The statistical population of the research consisted of two sections, in the first section, all the customers of Iran Khodro Company in the 5 districts of Tehran, and in the second section, the employees of the agencies in the mentioned areas were included. 384 people and 50 people were selected based on available random sampling in the customer section using non-probability quota sampling method. Regarding the theoretical foundations and background of the research, using library resources and in the field part, the tool for collecting information is a standard questionnaire. The data were analyzed by structural equation modeling using Smart PLS software. The results of research hypotheses indicate that social media marketing, service innovation has an effect on value co-creation from both customers and employees, and the effect of social support on value co-creation is confirmed by employees but not by customers. Not approved. Therefore, focusing on innovation in services, organizations should try to strengthen value co-creation through social media marketing and social support from both the perspective of employees and customers. Manuscript profile
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  5 - Examining the Role of a Community’s Social Media-based Destination Brand in Winning Tourists’ Hearts Towards Co-Creating Values and Visiting the Place
  Zohreh Ali Esmaili Armin Goli
  10.61186/journalitor.36134.11.23.155
  This study sought to investigate the role of a community’s social media-based destination brand in winning the tourists’ hearts and convincing them to co-create values and visit the community. The population of this applied survey study comprised of Ramsar visitors who More

  This study sought to investigate the role of a community’s social media-based destination brand in winning the tourists’ hearts and convincing them to co-create values and visit the community. The population of this applied survey study comprised of Ramsar visitors who discussed it as a travel destination on social media and had used social media to choose Ramsar as a tourist destination. In this regard, 73 media sources where Ramsar had been discussed were selected using a judgmental sampling method. The required data were collected through electronic questionnaires from 384 visitors (out of 450 visitors) who were selected through non-probability convenient sampling. The collected data were then analyzed via SmartPLS software using structural equation modeling and path analysis technique. The findings of the study suggested that a community’s social media-based destination brand had a positive impact on the visitors’ enjoyment of the place, loving the place, and positive surprise towards the destination, persuading them to participate in the co-creation of values and thus revisit the place. Manuscript profile
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  6 - Image Fake News Detection using Efficient NetB0 Model
  Yasmine Almsrahad Nasrollah  Moghaddam Charkari
  10.61186/jist.40976.12.45.41
  Today, social networks have become a prominent source of news, significantly altering the way people obtain news from traditional media sources to social media. Alternatively, social media platforms have been plagued by unauthenticated and fake news in recent years. How More

  Today, social networks have become a prominent source of news, significantly altering the way people obtain news from traditional media sources to social media. Alternatively, social media platforms have been plagued by unauthenticated and fake news in recent years. However, the rise of fake news on these platforms has become a challenging issue. Fake news dissemination, especially through visual content, poses a significant threat as people tend to share information in image format. Consequently, detecting and combating fake news has become crucial in the realm of social media. In this paper, we propose an approach to address the detection of fake image news. Our method incorporates the error level analysis (ELA) technique and the explicit convolutional neural network of the EfficientNet model. By converting the original image into an ELA image, it is possible to effectively highlight any manipulations or discrepancies within the image. The ELA image is further processed by the EfficientNet model, which captures distinctive features used to detect fake image news. Visual features extracted from the model are passed through a dense layer and a sigmoid function to predict the image type. To evaluate the efficacy of the proposed method, we conducted experiments using the CASIA 2.0 dataset, a widely adopted benchmark dataset for fake image detection. The experimental results demonstrate an accuracy rate of 96.11% for the CASIA dataset. The results outperform in terms of accuracy and computational efficiency, with a 6% increase in accuracy and a 5.2% improvement in the F-score compared with other similar methods. Manuscript profile
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  7 - A comprehensive survey on the influence maximization problem in social networks
  mohsen taherinia mahdi Esmaeili Behrooz Minaei
  With the incredible development of social networks, many marketers have exploited the opportunities, and attempt to find influential people within online social networks to influence other people. This problem is known as the Influence Maximization Problem. Efficiency a More

  With the incredible development of social networks, many marketers have exploited the opportunities, and attempt to find influential people within online social networks to influence other people. This problem is known as the Influence Maximization Problem. Efficiency and effectiveness are two important criteria in the production and analysis of influence maximization algorithms. Some of researchers improved these two issues by exploiting the communities’ structure as a very useful feature of social networks. This paper aims to provide a comprehensive review of the state of the art algorithms of the influence maximization problem with special emphasis on the community detection-based approaches Manuscript profile