@inproceedings{13322,
  abstract     = {{Previous research suggests the existence of sentiments in online social networks. In comparison to real life human interaction, in which sentiments have been shown to have an influence on human behaviour, it is not yet completely understood which mechanisms explain how sentiments influence users in online environments. We develop a theoretical framework that tries to bridge the gap between social influence theories that focus on offline interactions on one hand and online interaction in social networks on the other hand. We then test our hypothesis about the influence and dissemination of sentiments in a quantitative analysis that is based on retrieved textual messages of communication patterns in over 12000 online social networks. Our empirical results suggest a general influence of sentiments on node communication patterns that is evidenced by increased occurrences of subsequent messages that express the same sentiment polarization. We interpret these findings and suggest future research to advance our currently limited theories that assume perceived and generalized social influence to path-dependent social influence models that consider actual behaviour.}},
  author       = {{Hillmann, Robert and Trier, Matthias}},
  booktitle    = {{ECIS 2013 Proceedings}},
  isbn         = {{9783834924421}},
  keywords     = {{Social Network Analysis, Sentiment Analysis, Communication Patterns}},
  publisher    = {{Association for Information Systems. AIS Electronic Library (AISeL)}},
  title        = {{{Influence and Dissemination Of Sentiments in Social Network Communication Patterns}}},
  year         = {{2013}},
}

@inproceedings{13326,
  abstract     = {{Communication within online social network applications enables users to express and share sentiments electronically. Existing studies examined the existence or distribution of sentiments in online communication at a general level or in small-observed groups. Our paper extends this research by analyzing sentiment exchange within social networks from an ego-network perspective. We draw from research on social influence and social attachment to develop theories of node polarization, balance effects and sentiment mirroring within communication dyads. Our empirical analysis covers a multitude of social networks in which the sentiment valence of all messages was determined. Subsequently we studied ego-networks of focal actors (ego) and their immediate contacts. Results support our theories and indicate that actors develop polarized sentiments towards individual peers but keep sentiment in balance on the ego-network level. Further, pairs of nodes tend to establish similar attitudes towards each other leading to stable and polarized positive or negative relationships}},
  author       = {{Hillmann, Robert and Trier, Matthias}},
  booktitle    = {{AMCIS 2012 Proceedings}},
  editor       = {{Joshi, K.D. and Yoo, Youngjin}},
  keywords     = {{Social Network Analysis, Ego-Network Analysis, Node Polarization, Sentiment Dissemination}},
  publisher    = {{Association for Information Systems. AIS Electronic Library (AISeL)}},
  title        = {{{Sentiment Polarization and Balance among Users in Online Social Networks}}},
  volume       = {{24}},
  year         = {{2012}},
}

@inproceedings{13331,
  abstract     = {{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 patternsand 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 ofhierarchy 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.}},
  author       = {{Hillmann, Robert and Trier, Matthias}},
  booktitle    = {{Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining}},
  isbn         = {{9780769547992}},
  keywords     = {{Social Network Analysis, Dynamic Network Motif Analysis, Sentiment Dissemination, Networking Effects, Triads}},
  pages        = {{510--515}},
  publisher    = {{IEEE}},
  title        = {{{Dissemination Patterns and Associated Network Effects of Sentiments in Social Networks}}},
  year         = {{2012}},
}