پژوهشنامه پردازش و مدیریت اطلاعات (علوم و فناوری اطلاعات سابق)

The emergence of participatory social media has created a new ecosystem for the participation of users in social events (Fuchs, 2021) . Content exchange by the user generates values such as a social discourse and awareness of a special subject triggering political, social, and other types of changes (Edom, Hwang & Kim, 2018) . With tens of millions of active users, social media have turned into dynamic resources of people’s interests, needs, and beliefs, giving rise to a rich content reserve . This provides policymakers with a great opportunity to learn about citizens and communicate with them effectively (Simonofski & Burnay, 2021) . Social media serve as a link between users and policymakers, serving as a novel source to involve users in formulating and enacting policies (Driss, Mellouli & Trabelsi, 2019).Policymakers need to know the users’ opinions because users post their opinions on social media with minimal supervision (Dekker, van Den Brink & Meijer, 2019) . Users express their positive and negative opinions on various issues on social platforms, providing policymakers with a unique opportunity to improve communication with citizens and learn about their needs and opinions (De Paula, Dincelli & Harrison, 2018).

This essay examines the tripartite relationship between social media companies, policy regulators and the public interest. There are many complex issues to consider regarding regulation of social media companies. The author looks at all three areas separately to try and understand the motivations and expectations of each entity.

Social media websites like Twitter and Facebook have become a treasure trove of data. Even today, people have not been able to fully comprehend the consequences, both positive and negative, of being on these websites. We have modeled the risks associated with such websites as a function of the population, i.e., the number of accounts present, along the lines of the tragedy of commons. We have tracked the variations between the average Strogartz Watts local clustering coefficient, the variance of Strogartz Watts local clustering coefficient and the global clustering coefficient as the number of accounts in a database increases. Regarding the average local and global clustering coefficient, researchers observed an initial phase of rapid increase followed by a phase of a continuous relatively smaller increase in their values. The variance of the average local clustering coefficient shows an initial phase of significant variation followed by a phase of continuous reduction in its value. Thus, the increase in the population size increases the transitivity of the network, increasing the risk associated with data being leaked via the website. The purpose of this research study is to simulate the social media connections and identify the application of the concept of ‘tragedy of commons’ in the social media domain. The researchers have also tried to look at insights obtained from simulations from a network theory perspective. The scope of this research study is to look at the way the connections are made on social media depending on the common interests of the people who use social media platforms. Using network theory, the researchers have tried to find out the connections structures. The researchers have used a simulation approach using a program that was written in C language on a UNIX system. Additional accounts to a hypothetical database were simulated using this program.

In the world of big data and social-media-headed governance and policymaking, data analysis is judged based on the speed and accuracy of execution. This study attempts to modify the existing Association Rule Mining (ARM) techniques by improving the space constraints. Although most of the ARM research is primarily focused on computational efficiency, it has not considered the identification of either the optimal support or the confidence value. Selection of ideal support, as well as confidence value, is vital for the ‘ARM’s quality. However, with the large dataset availability, the space vector poses the latest challenge in processing. Identification of the optimal parameters adapted to the space model is non-deterministic in nature. This research will focus on a Grammatical Evolution (GE) Association Rule Miner (GE-ARM) to identify the optimal threshold parameters for mining quality rules. Simulations are done using the FoodMart2000 dataset, and then, the proposed method is compared against the Apriori, the Frequent Pattern (FP) growth, and the Genetic Algorithms (GA). Simulation results exhibit substantial enhancements in space and rules generated together with time complexity. Compared to Apriori and FP-tree methods, the proposed GE-ARM achieves lesser runtime by around 20%. Such an improvisation would categorically change the dynamics of social media analytics by reducing the space constraints and can have more significant ramifications in policymaking. Therefore, such an improvement is undoubtedly an effective nudge in policymaking.

The present paper discusses the change in accessibility and searchability of data due to the popularity of mobile app versions of social media. The main argument is that new social media platforms restrict the access of search engines to the user-generated contents that are created and exchanged within them, and such trends have made access to public content more difficult. Focusing on the phrases “platforms as information blockhole” and “burial of content”, this article is a conceptual paper that argues that in contrast with the idea of freedom of information and data in world-wide-web, today mobile app platforms have formed close-core databases that search engines are restricted to access to them. The article warns that due to the increasing popularity of social media platforms, a huge volume of information is being generated and exchanged within them and this leads to new discrimination in access to the information. It also stresses the necessity of new types of syndication contracts between search engines and platforms as a new business model; or new policies that guarantee the findability of generating and exchanging public data on social media platforms.

Nowadays, electronic word-of-mouth (eWOM) has become the primary source of tourism-related information. Travelers are increasingly seeking additional information provided in eWOM platforms to minimize the complexity and insecurity involved in making a purchase decision. However, there still is a lack of research on the impact of eWOM on travelers’ green hotel booking intentions. Therefore, this study aims to develop a theoretical model to examine the effects of positive and negative eWOM on travelers’ green hotel booking intentions and provide practical guidelines for hotel marketing and policymaking. To do this, a model was developed based on the theory of planned behavior (TPB) while positive and negative eWOM were linked to the model as two new factors. This study utilized a quantitative research approach and data collection was performed through an online survey questionnaire. Data was collected from 418 travelers who had the experience of searching on social media for collecting travel-related information. The statistical software SmartPLS and SPSS were used to analyze the data. Findings showed that customer attitudes, subjective norms, perceived behavioral controls, and positive eWOM positively influenced travelers’ green hotel booking intentions. In contrast, the influence of negative eWOM on travelers’ green hotel booking intentions was not supported. The findings of this study can assist hotel managers in social and content media policymaking. Meanwhile, they can help policymakers in the tourism industry develop optimum policies. This study can provide new capabilities for policymakers to address existing challenges and opportunities and promote green practices in the hotel sector.

This study examines (i) the role of social media functionalities in building trust (ii) and trust’s role in achieving co-production of the value proposition. This research confirms the positive impact of social media functionality on developing trust. A cross-sectional survey is conducted based on the questionnaire method in this study. The sample was drawn from Tehranand Arak  companies located in Science and Technology Parks and industrial zones. Structural equation modeling was performed to test the relationship among the research variables. Drawing upon a sample of 358 participants working in industrial firms and using partial least squares structural equation modeling, the functionality of social media as particular tools to build trust is elaborated.  Also, our research results prove the critical impact of trust on the co-production of value proposition dimensions, i.e., knowledge and information sharing, problem-solving, and co-production. Furthermore, it is shown that technological uncertainty has a positive moderating effect on the relationship between trust and co-production. Conversely, competition intensity has a negative moderating influence on the relationship between trust and problem-solving. The results of this study is particularly useful for B2B firms and shows that by investing in social media activities, they can extend their communications with their client and stakeholders to develop trust effectively. Such investment reaps the benefit of co-production of the value proposition. Based on the results, this paper suggests managerial implications for policymakers, sales managers, IT managers, and social media directors who wish to build a strong relationship with their clients and motivate them to take part in their production process and help them improve both quality and services.  

The use of ICT to support activities in the policymaking process is on the increase. At the inception of the COVID-19 pandemic, Government agencies around the world relied on ICTs to either remotely support and/or enable policy-making activities. Policy-making activities occur via collaborative processes between interested parties by means of dialogue. Some extant ICTs utilized by government agencies support and enable collaboration and dialogue. However, the decision on what ICT to adopt is not always easy as a result of the failure of some ICTs to support the task they were designed for. As a result due diligence is needed by public service administrators to decide on which ICT to adopt. This implies a decision process required to decide if the public agency will mobilize resources to acquire and implement the ICT. But as most government agencies around the world have adopted ICT to support dialogue and collaborative activities in their policy making decision. This paper provides the result of a study where the mobilization-decision theory was used to analyse and explain reasons why government agencies around the world, aside the pressure from COVID-19, made the decision to mobilize resources to acquire, implement and utilize ICTs for policy dialogue and collaboration.