The present study has been conducted to carry out a clickbait analysis of the educational tweets selected from the TED-ED account on Twitter. The current research investigates the analysis of tweets to examine the typical cues or features designed and used by writers to build an information gap to arouse the reader’s curiosity to click on the link to complete the missing information. To achieve the aim of the study, the researcher utilizes Chen's (2015) framework for detecting clickbait, which includes specific features or strategies such as the use of the unresolved pronoun, unanswered questions, the use of numerals, and so on. The study illustrates that in clickbait, the writer adheres to these strategies to fulfill his aims by provoking our curiosity. The study highlights the features used to identify potential clickbait text for readers and identify the occurrence of the most frequent one through the rate of tweets.