Social media is an interactive forum where people may exchange ideas, viewpoints, and information to discuss various topics and express their perspectives. In engineering education, social media is becoming more widely acknowledged and used, and studies have shown that it can involvement, learning, and engagement of the students. To develop policies for the efficient application of social media platforms in engineering education, the main topic of this theory paper is evaluating the numerous field research investigations by compiling the diverse research subjects, social media components that are employed, and analysis methods, among other things. The pieces for this study were obtained from a number of sources, such as Scopus, Science Direct, and Web of References: Science, Wiley Online Library, Google Scholar, IEEE Xplore Library, ERIC. As a component of this literature search, the search phrases used to retrieve articles from these databases are Snap chat + engineering + memes + pages; Youtube + engineering + stem Facebook + Engineering, Instagram + Engineering, and X(Twitter) + Engineering. The review process involved these distinct steps. In the first part a interview in the form of questionnaire were given on Instagram Polls feature to 10 Selected Top achiever programme students. The findings indicate that Facebook, Instagram, and X (Twitter) have been used as a learning environment in a few engineering disciplines, including software engineering, civil engineering, mechanical engineering, and electronics engineering. More than half of the sampled articles used quantitative research designs and descriptive statistics for data analysis, and META Facebook emerged as the most preferred choice of researchers among the sampled articles. Initially, all articles from various databases were gathered and compared to eliminate any duplicates, 10 articles that met the exclusion criteria as articles not focused on engineering, articles in languages other than English, articles with a focus other than Facebook, Instagram, and Twitter, and work-in-progress articles, were removed from the final list. In the second step, these 10 articles were screened based on their titles and abstracts to assess their relevance and applicability to the study. Out of these, 2 articles were selected for further consideration. Articles not meeting the relevance and applicability criteria were excluded from the study. In the third step articles that remained were critically reviewed to extract the relevant information necessary for the analysis.Information such as research questions, research design, data collection, and data analysis, among others, were retrieved from the articles and consolidated in a separate file. Finally, this consolidated information was further analyzed and synthesized to generate observations and trends.