@inproceedings{AbramovaGladkayaKrasnova2021,
  author    = {Abramova, Olga and Gladkaya, Margarita and Krasnova, Hanna},
  title     = {An unusual encounter with oneself},
  series = {ICIS 2021: IS and the future of work},
  booktitle = {ICIS 2021: IS and the future of work},
  publisher = {AIS Electronic Library (AISeL)},
  address   = {[Erscheinungsort nicht ermittelbar]},
  year      = {2021},
  abstract  = {Helping overcome distance, the use of videoconferencing tools has surged during the pandemic. To shed light on the consequences of videoconferencing at work, this study takes a granular look at the implications of the self-view feature for meeting outcomes. Building on self-awareness research and self-regulation theory, we argue that by heightening the state of self-awareness, self-view engagement depletes participants' mental resources and thereby can undermine online meeting outcomes. Evaluation of our theoretical model on a sample of 179 employees reveals a nuanced picture. Self-view engagement while speaking and while listening is positively associated with self-awareness, which, in turn, is negatively associated with satisfaction with meeting process, perceived productivity, and meeting enjoyment. The criticality of the communication role is put forward: looking at self while listening to other attendees has a negative direct and indirect effect on meeting outcomes; however, looking at self while speaking produces equivocal effects.},
  language  = {en}
}
@inproceedings{AbramovaGundlachBilda2021,
  author    = {Abramova, Olga and Gundlach, Jana and Bilda, Juliane},
  title     = {Understanding the role of newsfeed clutter in stereotype activation},
  series = {PACIS 2021 proceedings},
  booktitle = {PACIS 2021 proceedings},
  number    = {473},
  publisher = {AIS Electronic Library (AISeL)},
  address   = {[Erscheinungsort nicht ermittelbar]},
  isbn      = {978-1-7336325-7-7},
  year      = {2021},
  abstract  = {Despite the phenomenal growth of Big Data Analytics in the last few years, little research is done to explicate the relationship between Big Data Analytics Capability (BDAC) and indirect strategic value derived from such digital capabilities. We attempt to address this gap by proposing a conceptual model of the BDAC - Innovation relationship using dynamic capability theory. The work expands on BDAC business value research and extends the nominal research done on BDAC - innovation. We focus on BDAC's relationship with different innovation objects, namely product, business process, and business model innovation, impacting all value chain activities. The insights gained will stimulate academic and practitioner interest in explicating strategic value generated from BDAC and serve as a framework for future research on the subject},
  language  = {en}
}
@inproceedings{Abramova2020,
  author    = {Abramova, Olga},
  title     = {Does a smile open all doors?},
  series = {Proceedings of the 53rd Hawaii International Conference on System Sciences},
  booktitle = {Proceedings of the 53rd Hawaii International Conference on System Sciences},
  publisher = {HICSS Conference Office University of Hawaii at Manoa},
  address   = {Honolulu},
  isbn      = {978-0-9981331-3-3},
  pages     = {831 -- 840},
  year      = {2020},
  abstract  = {Online photographs govern an individual's choices across a variety of contexts. In sharing arrangements, facial appearance has been shown to affect the desire to collaborate, interest to explore a listing, and even willingness to pay for a stay. Because of the ubiquity of online images and their influence on social attitudes, it seems crucial to be able to control these aspects. The present study examines the effect of different photographic self-disclosures on the provider's perceptions and willingness to accept a potential co-sharer. The findings from our experiment in the accommodation-sharing context suggest social attraction mediates the effect of photographic self-disclosures on willingness to host. Implications of the results for IS research and practitioners are discussed.},
  language  = {en}
}
@inproceedings{HagemannAbramova2022,
  author    = {Hagemann, Linus and Abramova, Olga},
  title     = {Crafting audience engagement in social media conversations},
  series = {Proceedings of the 55th Hawaii International Conference on System Sciences},
  booktitle = {Proceedings of the 55th Hawaii International Conference on System Sciences},
  publisher = {HICSS Conference Office University of Hawaii at Manoa},
  address   = {Honolulu},
  isbn      = {978-0-9981331-5-7},
  pages     = {3222 -- 3231},
  year      = {2022},
  abstract  = {Observing inconsistent results in prior studies, this paper applies the elaboration likelihood model to investigate the impact of affective and cognitive cues embedded in social media messages on audience engagement during a political event. Leveraging a rich dataset in the context of the 2020 U.S. presidential elections containing more than 3 million tweets, we found the prominence of both cue types. For the overall sample, positivity and sentiment are negatively related to engagement. In contrast, the post-hoc sub-sample analysis of tweets from famous users shows that emotionally charged content is more engaging. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with a vast number of followers. Prosocial orientation ("we-talk") is consistently associated with more likes, comments, and retweets in the overall sample and sub-samples.},
  language  = {en}
}
@article{HagemannAbramova2023,
  author    = {Hagemann, Linus and Abramova, Olga},
  title     = {Emotions and information diffusion on social media},
  series = {AIS transactions on replication research},
  volume    = {9},
  journal   = {AIS transactions on replication research},
  number    = {1},
  publisher = {AIS},
  address   = {Atlanta},
  issn      = {2473-3458},
  doi       = {10.17705/1atrr.00079},
  pages     = {1 -- 19},
  year      = {2023},
  abstract  = {This paper presents a methodological and conceptual replication of Stieglitz and Dang-Xuan's (2013) investigation of the role of sentiment in information-sharing behavior on social media. Whereas Stieglitz and Dang-Xuan (2013) focused on Twitter communication prior to the state parliament elections in the German states Baden-Wurttemberg, Rheinland-Pfalz, and Berlin in 2011, we test their theoretical propositions in the context of the state parliament elections in Saxony-Anhalt (Germany) 2021. We confirm the positive link between sentiment in a political Twitter message and its number of retweets in a methodological replication. In a conceptual replication, where sentiment was assessed with the alternative dictionary-based tool LIWC, the sentiment was negatively associated with the retweet volume. In line with the original study, the strength of association between sentiment and retweet time lag insignificantly differs between tweets with negative sentiment and tweets with positive sentiment. We also found that the number of an author's followers was an essential determinant of sharing behavior. However, two hypotheses supported in the original study did not hold for our sample. Precisely, the total amount of sentiments was insignificantly linked to the time lag to the first retweet. Finally, in our data, we do not observe that the association between the overall sentiment and retweet quantity is stronger for tweets with negative sentiment than for those with positive sentiment.},
  language  = {en}
}