Cyberbullying is widely used nowadays in electronic communication. It takes different forms, and it is considered a serious problem that faces all communities. Therefore, the current study is an attempt to discover cyberbullying with its types found in one type of electronic communication, “Facebook”. The data are as type of screenshots and collected from an archived formal page on Facebook called “BBC News”. The data of the study encompass (10 comments) samples “screen shots” from different posts on “BBC News”. The analyses reveal  “four” different types of cyberbullying which are employed in the data. The types are flaming, which is a reply directed towards other people’s comments; rumour spreading which is directed towards the posts or the channel; trolling, which is directed towards a specific post or the topic of discussion; and tagging, which occurs by making tags to other people with their usernames. Thus, cyberspace creates new different social environments that allow different online users from all over the world to contribute to electronic communication and cause many forms of cyberbullying.

Since offensive language, words and expressions are widely used nowadays on the internet; the current paper is an attempt to discover and investigate offensive language that is used in one medium of electronic communication, which is “chatgroups”. The study focuses on analyzing and explaining offensive words and expressions found in chatgroups with their types and functions. The data of this study are a type of screenshots, (20) screenshots are randomly gathered from synchronous chatrooms. The analyses reveal different types of offensive language; these types are (vulgarity, insult, epithet, taboo, obscenity, and profanity). Besides, the functions of these offensive words and expressions are (body part, sexual, connotative, metaphoric, and expletive).

The current study is a quantitative-qualitative, descriptive, contrastive study of emoticons/smileys in English and Arabic netspeak “chatgroups”. It is an attempt to investigate different types of simleys in both languages with their meanings and functions. The data of this paper are gathered through screenshots from synchronous chatgroups that occur in real time. The size of the data is (50) screenshots, and each language has (25). The findings reveal that simleys/emoticons are widely used in both languages. It appears that English has (15) whereas Arabic has (18) different types. In English, chatters tend to use a single emoticon mostly at the end of the sentence, whereas in Arabic, chatters tend to use combinations of smileys instead of words or sentences. This indicates that using smileys is different between English and Arabic chatters. The simleys that are found in both languages have similar meanings. The functions of these smileys are also similar in both languages, but from similey to smiley.