Social networking

The study intended to examine the effects of Telegram on Iranian EFL learners' vocabulary knowledge and the attitude of them towards vocabulary learning. To this end, a group of 100 Iranian advanced EFL learners participated in an experimental design project. The participants were selected after they took the Oxford Quick Placement Test and they were divided into experimental and control groups. The participants of both groups had a three-week vocabulary instruction. The treatment was similar for both groups except for exercises done after the class. The participants in the experimental group were asked to fill out an attitudinal questionnaire after the treatment. Then, a vocabulary test was administered among the participants of both groups. Results of the independent-samples t-test run on the collected data indicated that participants of the experimental group outperformed those of the control group. The findings of the attitudinal questionnaire showed that the participants had positive attitude toward using Telegram. The conclusion drawn is that those in the experimental group were free in using the online group to interact with each other. Within this framework, learners in the experimental group indicated that they enjoyed this instruction as it was fun to embark on new technological learning methods

Today, social networks are fast and dynamic communication intermediaries that are a vital business tool. This study aims at examining the views of those involved with Facebook stocks so that we can summarize their views to predict the general behavior of this stock and collectively consider possible Facebook stock price movements, and create a more accurate pattern compared to previous patterns. In this study, we have analyzed two statistical samples, the first being a large dataset containing a variety of tweets with an emotional tag. That is, it needed a set that had already been extracted from each individual tweet by a trusted human or machine. Consequently, we have collected posts on Facebook in an eighty-day period. In this study, we used a tagged dataset using Python's programming language and vector-to-word algorithm. The research results show that, we need stock change information, machine learning and sentiment analysis, and on paper we conclude that positive news about a company excites people to have positive opinions about it which in turn results in people encouraging each other to buy and hold stocks. Meanwhile, the opposite trend is also true, but everything will not always be easy and clear, and it is in areas of high complexity and mental uncertainty that the art of using the three elements mentioned above is evident.

Purpose: Digital literacy fosters social advantages such as chances to interact with others and forge and develop social relationships by enabling online activities and leading to online social capital development. This study investigated the relationship between digital literacy and online social capital. Methodology: The research method is quantitative, descriptive, cross-sectional, and correlational. Participants comprised 754 (520 female and 234 male) students of Tabriz universities during the months of June and August 2023, who were randomly selected from among those willing to cooperate and responded to the Digital Literacy Questionnaire (Ng, 2012) and Online Social Capital Questionnaire (Duradoni et al., 2022). Data were analyzed using confirmatory factor analysis and structural equation modelling with SPSS version 27 and Amos Graphic version 24 software. Findings: Utilizing confirmatory factor analysis, the factorial structure of the research instruments was examined. The digital literacy questionnaire's three-factor structure and the online social capital questionnaire's two-factor structure were confirmed. The GFIs were higher than 0.9, and the RMSEA was below 0.08. The fit indices indicate that the structural model describing the relationship between digital literacy and online social capital is supported. The standard weights of the confidence and connectedness dimensions of the relationship between digital literacy and online social capital were 0.42 and 0.48, respectively (p<0.05). Conclusion: Digital literacy encompasses social, cognitive, and emotional skills in addition to technical ones. Therefore, digital literacy is multidimensional and lays the foundation for a new, constantly evolving style of online relationships and interpersonal connections. Higher levels of digital literacy and its components provide individuals with the ability and opportunity to convert their network of relationships into other forms of capital, obtain and provide support in the virtual space, and engage in emotional exchange, group leisure time, counselling, and collaboration. These competencies form the basis of online social capital.

The positive effect of social networking, particularly social networking sites (SNSs), on improving the process of learning has been acknowledged by many recent types of research. The relationship between features and characteristics of SNSs and the development of students' social networking was of interest to past researchers. As social networking is primarily perceived as intelligent thought and action in both real and virtual environments, there seems to be a need for a qualitative exploration of the influential factors of students' social networking. The study has been conducted using the case study method to look at the identified factors retrieved from previous research. A semi-structured in-depth interview was used to investigate the viewpoints and experiences of socially proactive and successful students at Iranian universities. Findings explain students' social networking due to three factors categorized as central, causal, and contextual. The personal learning system has a critical position among the various factors affecting students' social networking. Therefore, despite the facilitating role of social networking in promoting the learning process, students' social networking would be useless without utilizing a personal learning system. We can see a dynamic and interactive cycle of learning and social networking in the university context. The research has been founded on critical consideration of previously studied factors affecting social networking that were mainly limited to online technologies according to qualitative exploration. As a result of this research, different learning and social networking levels regarding diverse meaning, function, and complexity were identified.