This paper identified and explored how Iranian Twitter users framed Iran 2017 presidential election in a networked practice. Employing networked framing theory, we tried to identify which subjects were framed by networked publics on Persian Twitter. Moreover, we analyzed the similarities and differentiates in framing the election by different networked publics. We combined social network analysis, ethnographic content analysis and social media critical discourse study approach. First, we collected 2596284 tweets during the election period. Then, we focused on retweet (RT) network as the information diffusion network, and discovered networked publics by applying cluster analysis on this corpus. Afterwards, we identified 50 top influential users in each cluster based on their Page Ranks. Finally, we collected all tweets of these users in the whole network and analyzed them. We used three coders to code the selected sample of 10416 tweets in three rounds. Results showed that ‘ Election campaigns’ , Candidates and their fans ethical practices’ , ‘ Corruption’ , and ‘ Candidates’ qualifications’ were the most dominant networked frames. Furthermore, ordinary users were mainly responsible in framing these subjects.