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This article reviews the influence of netizen comments on the mental health of parents of children with special needs. The research analyzed in the article is based on the background of the problem that negative comments have a significant impact on the mental health of parents with disabilities, so this research aims to address the stigmatization and discrimination of persons with disabilities and their families on social media and encourage people to treat them with the same respect and understanding as other people. This type of research is qualitative research with a naturalistic paradigm. The method used in the assignment article for the Indonesian Language Education course is a systematic literature review (SLR). The research instrument is a survey and the researcher is the key instrument. The data source for this research is the results of a survey of several comments on the social media accounts of parents of children with special needs. The result is making learning media in the form of posters or videos, and others about the effect of bad comments on the mental health of parents of children with special needs as well as the importance of being responsible and being wise in writing comments on social media.

Technological developments today make it easy for people to use social media as a means of expressing opinions, including Twitter. The case study taken by the researcher is the sentiment towards the performance of the mayor of Medan. The case was taken because it was widely discussed by Indonesian people, especially the city of Medan on Twitter social media. One of the uses of this research is to find out the trend of Twitter user comments on the performance of the mayor of Medan by conducting a sentiment analysis. Sentiment will be classified as positive, negative and neutral. The algorithm used in sentiment analysis is Naïve Bayes. The stages in conducting sentiment analysis in this study are data preprocessing, data processing, classification, and evaluation. The results of this study are using the SMOTE method, the training and testing ratio is 80:20 because it has the highest accuracy, which is 78% compared to other ratios. The prediction results resulting from the classification turned out to be more dominant towards neutral labels. In addition to classifying for sentiment analysis, this study also measures the performance of the model created. The results showed that the Naïve Bayes algorithm has a precision value of 78%, a recall of 78%, and an f1-score of 77%.

In this discussion, we are interested in making this study because the language used on social media tends to use slang and non-standard words that are influenced by culture, regional languages, and language absorption from other social media, therefore this study was held to provide information to people, especially adolescents, to start using good and correct Indonesian. This study aims to determine the use of Indonesian on social media. Data is obtained from status, stories, and conversations in the comments column on Twitter and Instagram that are taken randomly. 

This article considers how the use of Indonesian on social instagram through west Java governor @ridwankamil's account. Where this instagram is being used as one means to showcase his identity as an active politician using a mixed language between Indonesian and sundanese. The study aims to know the language used by ridwan kamil in every post he posted. The study used a method with a library study type. This library study process is also used for collecting data. Based on results and discussions, analysis of the use of language styles or variations in social media has been found in a great variety of language styles such as the use of sundanese in his posts and comments column, through his personal instagram of @ridwankamil, through his personal instagram not only uploading political content but also by interacting with his followers through the instagram so that personal messages can be faster and more accessible.