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News is a kind of writing style, which is so valuable that many linguists choose it to study. This thesis aims to conduct a systemic analysis of modality type, value and orientation under the framework of Halliday's Systemic-functional Grammar in order to explore the interpersonal meanings of modality in English news discourse. The research data is drawn from microblogging official platforms, among which 20 pieces of news discourse in all are selected to establish a small type of corpus. All the 20 pieces of news discourse are taken from the microblogging in 1.20 to 2.20 of 2017. All the news is about "Donald Trump's Muslim Entry Ban" (A ban made by Donald Trump, which claimed that Muslim can't enter America). Meanwhile, both qualitative and quantitative research methods are adopted to discover the distribution of modality in micro-blogging news discourse and its interpersonal meanings, and hence to deepen people's cognition and understanding on micro-blogging news discourse. Through a detailed analysis, the study has a lot of findings. We found that modality language is widely used in micro-blogging news. From the perspective of modality type, reporters prefer to use finite modal adjunct such as "will" in the type of modulation to show their emotional attitude of the target thing. From the perspective of modality value, we can see that median value is the most popular among three values for reporters, and "will" and "would" are the most popular expressions that express the speaker's expectations, willingness and determination or the reporter's views, attitudes on the possibility of a certain event. Meanwhile, from the perspective of modality orientation, the speaker or writer tends to use implicit objective orientation in order to show objectiveness of the news discourse and get rid of writers' responsibilities. This paper attempts to analyze modality in micro-blogging English news discourse from the perspective of interpersonal functions which aims to provide a new method for discourse analysis and acts as a beneficial complementary to modality language analysis.