Review: The role of emotion in computer-mediated communication: A review
Computers in Human Behavior
Local Topology of Social Network Based on Motif Analysis
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
User interactions in social networks and their implications
Proceedings of the 4th ACM European conference on Computer systems
Patterns and dynamics of users' behavior and interaction: Network analysis of an online community
Journal of the American Society for Information Science and Technology
Exploring changes in network structures during online discussions
ICLS'08 Proceedings of the 8th international conference on International conference for the learning sciences - Volume 1
Data mining emotion in social network communication: Gender differences in MySpace
Journal of the American Society for Information Science and Technology
Predicting positive and negative links in online social networks
Proceedings of the 19th international conference on World wide web
Sentiment in short strength detection informal text
Journal of the American Society for Information Science and Technology
Happiness is assortative in online social networks
Artificial Life
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Communication in online social networks has been analyzed for some time regarding the expression of sentiments. So far, very little is known about the relationship between sentiments and network emergence, dissemination patterns and possible differences between positive and negative sentiments. The dissemination patterns analyzed in this study consist of network motifs based on triples of actors and the ties among them. These motifs are associated with common social network effects to derive meaningful insights about dissemination activities. The data basis includes several thousand social networks with textual messages classified according to embedded positive and negative sentiments. Based on this data, sub-networks are extracted and analyzed with a dynamic network motif analysis to determine dissemination patterns and associated network effects. Results indicate that the emergence of digital social networks exhibits a strong tendency towards reciprocity, followed by the dominance of hierarchy as an intermediate step leading to social clustering with hubs and transitivity effects for both positive and negative sentiments to the same extend. Sentiments embedded in exchanged textual messages do only play a secondary role in network emergence and do not express differences regarding the emergence of network patterns.