Generalized Nets: A New Approach to Model a Hashtag Linguistic Network on Twitter

摘要: In the last few years micro-blogging platform Twitter has played a significant role in communication of civil uprisings, political events or natural disasters. One reasons is adoption hashtag, which represents short word phrase that follows hash sign (\(\#\)). These semantic elements captured topics behind tweets and allowed information flow to bypass traditional social network structure. The hashtags provide way for users embed metadata their posts achieving several important communicative functions: they can indicate specific domain post, link post an existing topic, range complex meanings media texts. this paper, Generalized nets are applied as tool model structural characteristics hashtag linguistic through possible communities interests emerge, investigate propagation patterns resulting from uncoordinated actions underlying space. (GN) extensions Petri by providing functional topological aspects unavailable nets. study networks generalized perspective enables us deeper manner each element GN, substituting it with another, more detailed order be examined depth. result improved understanding connections data ability dynamically add new details expand discover complexities unable discovered analysis due prohibitive computational cost. Analysis performed on collection Tweets results presented.