Tanulmányok
Present paper aims to show the fundamental research areas of network science and also describes current research topics of this new, emerging science. The second part of the paper shows the connections between linguistics and network research. The paper describes problematic issues of linguistics network research done by non-linguists and also mentiones emerging fields on the crossroads of linguistics and network research.
With respect to mathematical graph theory and network theory, this study examines language from four aspects (‘small world’ concept, scale-free networks, mutual embeddedness and ‘weak ties’ concept), thus revealing its structural and operational network characteristics. The ideas and analogies of cognitivists and network researchers (again) suggest overlaps between natural and social sciences. In fact they envisage an evolving super science, in which cross-science linguistics may become central. It seems that linguistics (again) (can) have an important role among disciplines and sciences studying humans, society and culture.
Lexis and grammar cannot be viewed as independently functioning entities any longer but rather as complementary network systems which merge to create meaning. Co-selection blurs the border between words to create extended units of meaning at the intersection of the lexical, grammatical, semantic and pragmatic network made visible on the vertical axis of a concordance. On the example of the lexical unit helyzet the present paper investigates the formation of extended units of meaning.
Internet and online communication have become an integrated part of our everyday life. This new type of communication call for new forms of information sharing and spreading. Consequently, there is an emerging need for analyzing and modeling such information sharing and spreading processes. In our work, we analyzed the data provided by Happy flu information spreading experiment, carried out in the blogosphere. We analyzed the structure, the growth, and the categories (topics) in the network in order to uncover the spreading mechanisms. We found, that categories in close relationship with the character of the experiment are frequent and spread along the main nodes in the branches. Propagation is not uniformly distributed in time: time intervals with intense and rare propagation events are present. Time intervals with intense propagation are in coincidence with the appearance of one or more new categories.