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Open Access Article

1 - The Geo-discourse of Takfiri IS group and its Media Representation- with emphasis on digital media

This essay would explore the media dimension of operations of takfiri-terrorist IS group. To do so we will study the discourse making process of IS throughout virtual space and Virtual Networks. This article argues that establishing a discoursive system and articulating More

This essay would explore the media dimension of operations of takfiri-terrorist IS group. To do so we will study the discourse making process of IS throughout virtual space and Virtual Networks. This article argues that establishing a discoursive system and articulating ideational concepts that construct the positions of Self and Other and give them a hegemonic status is possible via virtual networks and with enjoying of media ploys. In this regard the main question of this essay is about the evaluation of the level of efficacy of these media arenas for IS and assesing the opportunities or by contrast the threats offered by them for IS’s activism. Our hypothesis is that virtual space is useful for IS and this group thanks to a professional approach to social networks and knowing the function of media, can establish a media terrorism by psychological operation and therefore complete its geopolitics actions. Manuscript profile

Open Access Article

2 - Spam Detection in Twitter by Ensemble Learning Approach
Maryam Fasihi Mohammad Javad shayegan zahra hosieni zahra sejdeh

Today, social networks play a crucial role in disseminating information worldwide. Twitter is one of the most popular social networks, with 500 million tweets sent on a daily basis. The popularity of this network among users has led spammers to exploit it for distributi More

Today, social networks play a crucial role in disseminating information worldwide. Twitter is one of the most popular social networks, with 500 million tweets sent on a daily basis. The popularity of this network among users has led spammers to exploit it for distributing spam posts. This paper employs a combination of machine learning methods to identify spam at the tweet level. The proposed method utilizes a feature extraction framework in two stages. In the first stage, Stacked Autoencoder is used for feature extraction, and in the second stage, the extracted features from the last layer of Stacked Autoencoder are fed into the softmax layer for prediction. The proposed method is compared and evaluated against some popular methods on the Twitter Spam Detection corpus using accuracy, precision, recall, and F1-score metrics. The research results indicate that the proposed method achieves a detection of 78.1%. Overall, the proposed method, using the majority voting approach with a hard selection in ensemble learning, outperforms CNN, LSTM, and SCCL methods in identifying spam tweets with higher accuracy. Manuscript profile

Open Access Article

3 - Using Sentiment Analysis and Combining Classifiers for Spam Detection in Twitter
mehdi salkhordeh haghighi Aminolah Kermani

The welcoming of social networks, especially Twitter, has posed a new challenge to researchers, and it is nothing but spam. Numerous different approaches to deal with spam are presented. In this study, we attempt to enhance the accuracy of spam detection by applying one More

The welcoming of social networks, especially Twitter, has posed a new challenge to researchers, and it is nothing but spam. Numerous different approaches to deal with spam are presented. In this study, we attempt to enhance the accuracy of spam detection by applying one of the latest spam detection techniques and its combination with sentiment analysis. Using the word embedding technique, we give the tweet text as input to a convolutional neural network (CNN) architecture, and the output will detect spam text or normal text. Simultaneously, by extracting the suitable features in the Twitter network and applying machine learning methods to them, we separately calculate the Tweeter spam detection. Eventually, we enter the output of both approaches into a Meta Classifier so that its output specifies the final spam detection or the normality of the tweet text. In this study, we employ both balanced and unbalanced datasets to examine the impact of the proposed model on two types of data. The results indicate an increase in the accuracy of the proposed method in both datasets. Manuscript profile

Open Access Article

4 - A New Hybrid Method Based on Intelligent Algorithms for Intrusion Detection in SDN-IoT
Zakaria Raeisi Fazlloah Adibnia Mahdi Yazdian

In recent years, the use of Internet of Things in societies has grown widely. On the other hand, a new technology called Software Defined Networks has been proposed to solve the challenges of the Internet of Things. The security problems in these Software Defined Networ More

In recent years, the use of Internet of Things in societies has grown widely. On the other hand, a new technology called Software Defined Networks has been proposed to solve the challenges of the Internet of Things. The security problems in these Software Defined Networks and the Internet of Things have made SDN-IoT security one of the most important concerns. On the other hand, the use of intelligent algorithms has been an opportunity that these algorithms have been able to make significant progress in various cases such as image processing and disease diagnosis. Of course, intrusion detection systems for SDN-IoT environment still face the problem of high false alarm rate and low accuracy. In this article, a new hybrid method based on intelligent algorithms is proposed. The proposed method integrates the monitoring algorithms of frequent return gate and unsupervised k-means classifier in order to obtain suitable results in the field of intrusion detection. The simulation results show that the proposed method, by using the advantages of each of the integrated algorithms and covering each other's disadvantages, has more accuracy and a lower false alarm rate than other methods such as the Hamza method. Also, the proposed method has been able to reduce the false alarm rate to 1.1% and maintain the accuracy at around 99%. Manuscript profile

Open Access Article

5 - Improving polarity identification in sentiment analysis using sarcasm detection and machine learning algorithms in Persian tweets
Shaghayegh hajiabdollah Mitra Mirzarezaee Mir Mohsen Pedram

Sentiment analysis is a branch of computer science and natural language processing that seeks to familiarize machines with human emotions and make them recognizable. Both sentiment analysis and sarcasm which is a sub-field of the former, seek to correctly identify the h More

Sentiment analysis is a branch of computer science and natural language processing that seeks to familiarize machines with human emotions and make them recognizable. Both sentiment analysis and sarcasm which is a sub-field of the former, seek to correctly identify the hidden positive and negative emotions of the text. The use of sarcasm on social media, where criticism can be exercised within the context of humor, is quite common. Detection of sarcasm has a special effect on correctly recognizing the polarization of an opinion, and thus not only it can help the machine to understand the text better, but also makes it possible for the respective author to get his message across more clearly. For this purpose, 8000 Persian tweets that have emotional labels and examined for the presence or absence of sarcasm have been used. The innovation of this research is in extracting keywords from sarcastic sentences. In this research, a separate classifier has been trained to identify irony of the text. The output of this classifier is provided as an added feature to the text recognition classifier. In addition to other keywords extracted from the text, emoticons and hashtags have also been used as features. Naive Bayes, support vector machines, and neural networks were used as baseline classifiers, and finally the combination of classifiers was used to identify the feeling of the text. The results of this study show that identifying the irony in the text and using it to identify emotions increases the accuracy of the results. Manuscript profile

Open Access Article

6 - Investigating Twitter campaigns of Violence Against Women
shima nasertork ali delavar afsaneh mozaffari tahmores shiri

One of the most important topics that social networks -Twitter- have paid attention to is violence against women in Iran. The most important theoretical support in the emergence of these campaigns is the reflection of the texts about violence against women. One of the m More

One of the most important topics that social networks -Twitter- have paid attention to is violence against women in Iran. The most important theoretical support in the emergence of these campaigns is the reflection of the texts about violence against women. One of the most important factors in the emergence of such waves is the important activists in the field of these social networks, who use their followers to reflect these contents. The most important campaigns in terms of the number of tweets and retweets was the "Girls of the Revolution" campaign. The aim of the research is to analyze the performance of Twitter in reflecting the content of violence against women in Iran based on the most important campaigns that have emerged in the last decade. This issue was analyzed based on the theoretical foundations of types of violence and networked movements. The research method is the content analysis of tweets and hashtags related to campaigns from 2016 to 2016. The research results showed that the most important themes are about social and political violence against women. In this regard, some campaigns and hashtags have caused insecurities in the society the most important of which was the campaign of the girls of Enghelab Street in terms of the number of tweets and retweets. the analysis of the themes of tweets showed the absence of news, posts and tweets of people related to campaigns and hashtags. Manuscript profile

Open Access Article

7 - Sociological Analysis of the Cultural Components of Marriage in Persian Tweets
zahra sheikh Bagher saroukhani khadijeh zolghadr

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Sociological Analysis of the Cultural   Components of Marriage in Persian Tweets       Zahra Sheikh<a style="mso-footnote-id: ftn1;" title="" href="#_ftn1" name="_ftnref1">*</a>   Baqer Sarukhani<a style="mso-footnote-id: ftn2;" title="" href="#_ftn2" name="_ftnref2">**</a>    Khadija Zulqadr<a style="mso-footnote-id: ftn3;" title="" href="#_ftn3" name="_ftnref3">***</a>   Introduction   Marriage is a fundamental institution in both the family and the broader social structure, evolving over time. Understanding this area is crucial for policymakers to grasp societal attitudes, perspectives, and to plan effectively based on societal conditions. The aim of this research was to extract and analyze attitudes and demands regarding the cultural component of "marriage." This component encompasses attitudes, values, and mental priorities of individuals concerning marriage. The research utilized a qualitative content analysis method, focusing on Persian-speaking users of the X social network and employing a comprehensive sampling method to analyze tweets related to marriage from September 2021 till March 2022.       Methodology   The research employed hermeneutic content analysis. Hermeneutic content analysis is typically used to describe phenomena when existing theories or literature are limited. This approach avoids preconceived concepts, allowing new concepts to emerge from the data. Researchers immerse themselves in the data to gain novel insights, a process known as "inductive concept formation." Data analysis begins with repeated readings to achieve a comprehensive understanding. The researchers’ initiates analysis based on their perception of the text, continuing until patterns emerge. This process often results in identifying patterns from the text and categorizing them based on similarities and differences.   In the pilot study, 150 keywords were manually extracted from 600 tweets related to marriage. Using machine learning, approximately 1,800 relevant tweets were identified. After an initial cleaning stage, each tweet was reviewed, and those suitable for analysis were retained, while the rest were discarded. Ultimately, 919 tweets remained for analysis. In the second stage, each tweet was summarized in one word, and these summaries were grouped into categories with key concepts (subtopics) identified. In the third step, related subtopics were analyzed and combined to extract themes. This process was repeated throughout the research. Four main themes were identified: individualism (341 tweets), life skills (211 tweets), economy (197 tweets), and tradition (170 tweets).       Findings   The analysis revealed that Persian-speaking users of X social network discussed a range of topics related to marriage, including individual rights, fluid relationships, independence, communication skills, self-awareness skills, spousal participation, unemployment, the social value of wealth, economic problems, women's rights, family control, marriage customs, and women's rights.   The central theme of these discussions is relationships—what constitutes a desirable relationship and its qualities. The concept of relationships discussed extends beyond formal, registered marriages to include informal relationships, friendships, cohabitation, emotional and sexual partners, concubine (motteh), long-distance relationships, and virtual relationships. Four main themes emerged from the analysis: individualism, life skills, economy, and tradition.   “Individualism” emphasizes the value of the individual as a person with rights and opinions. Sub-themes of individualism and personal preservation were grouped under this broader theme. “Life skills” refer to psychological and social abilities that enable individuals to manage themselves effectively, including communication skills, self-awareness skills, and spousal participation.   The “economy” theme highlighted concerns such as inflation, unemployment, and future uncertainties as inhibiting factors for marriage. Economic attitudes toward marriage reflect a desire for wealth acquisition through clever and inexpensive means, aligning with consumer capitalism. “Tradition” involves societal customs, norms, and restrictions regarding marriage, including family control, marriage customs, and women's rights. The main criticism is that traditions limit individual freedom and personal opinions. While individuality and personal choice are highly valued today, past customs are not widely accepted by newer generations who advocate for equal rights and responsibilities based on personal views rather than traditional norms.       Conclusion   The discourse on marriage on social network X aligns with Bauman's theory of liquid relationships and Saroukhani's theory of personalization. Liquid relationships refer to short-term, non-committal relationships outside the framework of formal marriage, where commitment is minimal. Analysis of tweet content shows that preserving individuality and the power of choice are top priorities for users. They make decisions based on personal preferences and circumstances, free from overarching narratives. However, these liquid relationships may lead to psychological insecurity and intensified individualism, potentially alienating the family from its emotional and generational functions as a social institution, thereby endangering societal health.     <div style="mso-element: footnote-list;"> <hr align="left" size="1" width="33%" /> <div id="ftn1" style="mso-element: footnote;"> <a style="mso-footnote-id: ftn1;" title="" href="#_ftnref1" name="_ftn1">*</a> PhD Student in Cultural Sociology, Tehran <a name="_Hlk175653928"></a>Science & Research Unit, Islamic Azad University, Tehran, Iran. Sheikh.zahra84@gmail.com </div> <div id="ftn2" style="mso-element: footnote;"> <a style="mso-footnote-id: ftn2;" title="" href="#_ftnref2" name="_ftn2">**</a> Corresponding Author: Professor of Sociology Department, Tehran Science & Research Unit, Islamic Azad University, Tehran, Iran. b.saroukhani@yahoo.com </div> <div id="ftn3" style="mso-element: footnote;"> <a style="mso-footnote-id: ftn3;" title="" href="#_ftnref3" name="_ftn3">***</a> Assistant Professor, Department of Women's Studies, Tehran Science & Research Unit, Islamic Azad University, Tehran, Iran. kzolghadr@srbiau.ac.ir </div> </div>   Manuscript profile

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