Network Science provides a framework to understand the large-scale discussions that happen on social media and their impact on society. However, a standard network model of a conversational network destroys the context that users are interacting …
If we want to model Twitter conversations with a network, we need to account for the context that users interact within. We propose a deep-learning approach to separating Twitter data out into contextualized networks. We then show that these contextualized networks have very different nodesets, topology, and central actors than observed in the non-contextualized networks. Our findings suggest that the dominant way of modeling social media conversations may be inaccurately portraying the nature of the conversations and the most important people in them.
Network Science provides a framework to understand the large-scale discussions that happen on social media and their impact on society. However, a standard network model of a conversational network destroys the context that users are interacting …