TY - JOUR A1 - Wilksch, Moritz A1 - Abramova, Olga T1 - PyFin-sentiment BT - towards a machine-learning-based model for deriving sentiment from financial tweets JF - International journal of information management data insights N2 - Responding to the poor performance of generic automated sentiment analysis solutions on domain-specific texts, we collect a dataset of 10,000 tweets discussing the topics of finance and investing. We manually assign each tweet its market sentiment, i.e., the investor’s anticipation of a stock’s future return. Using this data, we show that all existing sentiment models trained on adjacent domains struggle with accurate market sentiment analysis due to the task’s specialized vocabulary. Consequently, we design, train, and deploy our own sentiment model. It outperforms all previous models (VADER, NTUSD-Fin, FinBERT, TwitterRoBERTa) when evaluated on Twitter posts. On posts from a different platform, our model performs on par with BERT-based large language models. We achieve this result at a fraction of the training and inference costs due to the model’s simple design. We publish the artifact as a python library to facilitate its use by future researchers and practitioners. KW - sentiment analysis KW - financial market sentiment KW - opinion mining KW - machine learning KW - deep learning Y1 - 2023 U6 - https://doi.org/10.1016/j.jjimei.2023.100171 SN - 2667-0968 VL - 3 IS - 1 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Baum, Katharina A1 - Abramova, Olga A1 - Meißner, Stefan A1 - Krasnova, Hanna T1 - The effects of targeted political advertising on user privacy concerns and digital product acceptance BT - a preference-based approach JF - Electronic markets N2 - Online businesses are increasingly relying on targeted advertisements as a revenue stream, which might lead to privacy concerns and hinder product adoption. Therefore, it is crucial for online companies to understand which types of targeted advertisements consumers will accept. In recent years, users have been increasingly targeted by political advertisements, which has caused adverse reactions in media and society. Nonetheless, few studies experimentally investigate user privacy concerns and their role in acceptance decisions in response to targeted political advertisements. To fill this gap, we explore the magnitude of privacy concerns towards targeted political ads compared to “traditional” targeting in the product context. Surprisingly, we find no notable differences in privacy concerns between these data use purposes. In the next step, user preferences over ad types are elicited with the help of a discrete choice experiment in the mobile app adoption context. Our findings suggest that while targeted political advertising is somewhat less desirable than targeted product advertising, the odds of choosing an app are statistically insignificant between two data use purposes. Together, these results contribute to a better understanding of users’ privacy concerns and preferences in the context of targeted political advertising online. KW - online privacy KW - targeting KW - advertisement KW - DCE Y1 - 2023 U6 - https://doi.org/10.1007/s12525-023-00656-1 SN - 1019-6781 SN - 1422-8890 VL - 33 IS - 46 PB - Springer CY - Heidelberg ER - TY - CHAP A1 - Abramova, Olga A1 - Gladkaya, Margarita A1 - Krasnova, Hanna T1 - An unusual encounter with oneself BT - exploring the impact of self-view on online meeting outcomes T2 - ICIS 2021: IS and the future of work N2 - 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. Y1 - 2021 UR - https://aisel.aisnet.org/icis2021/is_future_work/is_future_work/16 PB - AIS Electronic Library (AISeL) CY - [Erscheinungsort nicht ermittelbar] ER - TY - JOUR A1 - Hagemann, Linus A1 - Abramova, Olga T1 - Sentiment, we-talk and engagement on social media BT - insights from Twitter data mining on the US presidential elections 2020 JF - Internet research N2 - Purpose Given inconsistent results in prior studies, this paper applies the dual process theory to investigate what social media messages yield audience engagement during a political event. It tests how affective cues (emotional valence, intensity and collective self-representation) and cognitive cues (insight, causation, certainty and discrepancy) contribute to public engagement. Design/methodology/approach The authors created a dataset of more than three million tweets during the 2020 United States (US) presidential elections. Affective and cognitive cues were assessed via sentiment analysis. The hypotheses were tested in negative binomial regressions. The authors also scrutinized a subsample of far-famed Twitter users. The final dataset, scraping code, preprocessing and analysis are available in an open repository. Findings The authors found the prominence of both affective and cognitive cues. For the overall sample, negativity bias was registered, and the tweet’s emotionality was negatively related to engagement. In contrast, in the sub-sample of tweets from famous users, emotionally charged content produced higher engagement. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with many followers. Collective self-representation (“we-talk”) is consistently associated with more likes, comments and retweets in the overall sample and subsamples. Originality/value The authors expand the dominating one-sided perspective to social media message processing focused on the peripheral route and hence affective cues. Leaning on the dual process theory, the authors shed light on the effectiveness of both affective (peripheral route) and cognitive (central route) cues on information appeal and dissemination on Twitter during a political event. The popularity of the tweet’s author moderates these relationships. KW - social media KW - engagement KW - data mining KW - big data Y1 - 2023 U6 - https://doi.org/10.1108/INTR-12-2021-0885 SN - 1066-2243 VL - 33 IS - 6 SP - 2058 EP - 2085 PB - Emeral CY - Bingley ER - TY - JOUR A1 - Abramova, Olga A1 - Batzel, Katharina A1 - Modesti, Daniela T1 - Collective response to the health crisis among German Twitter users BT - a structural topic modeling approach JF - International Journal of Information Management Data Insights N2 - We used structural topic modeling to analyze over 800,000 German tweets about COVID-19 to answer the questions: What patterns emerge in tweets as a response to a health crisis? And how do topics discussed change over time? The study leans on the goals associated with the health information seeking (GAINS) model, discerning whether a post aims at tackling and eliminating the problem (i.e., problem-focused) or managing the emotions (i.e., emotion-focused); whether it strives to maximize positive outcomes (promotion focus) or to minimize negative outcomes (prevention focus). The findings indicate four clusters salient in public reactions: 1) “Understanding” (problem-promotion); 2) “Action planning” (problem-prevention); 3) “Hope” (emotion-promotion) and 4) “Reassurance” (emotion-prevention). Public communication is volatile over time, and a shift is evidenced from self-centered to community-centered topics within 4.5 weeks. Our study illustrates social media text mining's potential to quickly and efficiently extract public opinions and reactions. Monitoring fears and trending topics enable policymakers to rapidly respond to deviant behavior, like resistive attitudes toward containment measures or deteriorating physical health. Healthcare workers can use the insights to provide mental health services for battling anxiety or extensive loneliness from staying home. KW - social media KW - Twitter KW - modeling KW - regulatory focus theory KW - crisis management KW - text mining Y1 - 2022 U6 - https://doi.org/10.1016/j.jjimei.2022.100126 SN - 2667-0968 VL - 2 IS - 2 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Abramova, Olga A1 - Gundlach, Jana A1 - Bilda, Juliane T1 - Understanding the role of newsfeed clutter in stereotype activation BT - the case of Facebook T2 - PACIS 2021 proceedings N2 - 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 Y1 - 2021 UR - https://aisel.aisnet.org/pacis2021/79 SN - 978-1-7336325-7-7 IS - 473 PB - AIS Electronic Library (AISeL) CY - [Erscheinungsort nicht ermittelbar] ER - TY - JOUR A1 - Abramova, Olga T1 - No matter what the name, we're all the same? BT - examining ethnic online discrimination in ridesharing marketplaces JF - Electronic markets N2 - Sharing marketplaces emerged as the new Holy Grail of value creation by enabling exchanges between strangers. Identity reveal, encouraged by platforms, cuts both ways: While inducing pre-transaction confidence, it is suspected of backfiring on the information senders with its discriminative potential. This study employs a discrete choice experiment to explore the role of names as signifiers of discriminative peculiarities and the importance of accompanying cues in peer choices of a ridesharing offer. We quantify users' preferences for quality signals in monetary terms and evidence comparative disadvantage of Middle Eastern descent male names for drivers and co-travelers. It translates into a lower willingness to accept and pay for an offer. Market simulations confirm the robustness of the findings. Further, we discover that females are choosier and include more signifiers of involuntary personal attributes in their decision-making. Price discounts and positive information only partly compensate for the initial disadvantage, and identity concealment is perceived negatively. KW - sharing economy KW - discrimination KW - racism KW - discrete choice experiment KW - stated preferences KW - social inclusion Y1 - 2022 U6 - https://doi.org/10.1007/s12525-021-00505-z SN - 1019-6781 SN - 1422-8890 VL - 32 SP - 1419 EP - 1446 PB - Springer CY - Heidelberg ER - TY - GEN A1 - Abramova, Olga A1 - Wagner, Amina A1 - Olt, Christian M. A1 - Buxmann, Peter T1 - One for all, all for one BT - social considerations in user acceptance of contact tracing apps using longitudinal evidence from Germany and Switzerland T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - We propose a conceptual model of acceptance of contact tracing apps based on the privacy calculus perspective. Moving beyond the duality of personal benefits and privacy risks, we theorize that users hold social considerations (i.e., social benefits and risks) that underlie their acceptance decisions. To test our propositions, we chose the context of COVID-19 contact tracing apps and conducted a qualitative pre-study and longitudinal quantitative main study with 589 participants from Germany and Switzerland. Our findings confirm the prominence of individual privacy calculus in explaining intention to use and actual behavior. While privacy risks are a significant determinant of intention to use, social risks (operationalized as fear of mass surveillance) have a notably stronger impact. Our mediation analysis suggests that social risks represent the underlying mechanism behind the observed negative link between individual privacy risks and contact tracing apps' acceptance. Furthermore, we find a substantial intention–behavior gap. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 167 KW - digital contact tracing KW - privacy calculus KW - longitudinal study KW - privacy risks KW - surveillance KW - intention-behavior gap Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-605856 SN - 1867-5808 ER - TY - JOUR A1 - Abramova, Olga A1 - Wagner, Amina A1 - Olt, Christian M. A1 - Buxmann, Peter T1 - One for all, all for one BT - social considerations in user acceptance of contact tracing apps using longitudinal evidence from Germany and Switzerland JF - International Journal of Information Management N2 - We propose a conceptual model of acceptance of contact tracing apps based on the privacy calculus perspective. Moving beyond the duality of personal benefits and privacy risks, we theorize that users hold social considerations (i.e., social benefits and risks) that underlie their acceptance decisions. To test our propositions, we chose the context of COVID-19 contact tracing apps and conducted a qualitative pre-study and longitudinal quantitative main study with 589 participants from Germany and Switzerland. Our findings confirm the prominence of individual privacy calculus in explaining intention to use and actual behavior. While privacy risks are a significant determinant of intention to use, social risks (operationalized as fear of mass surveillance) have a notably stronger impact. Our mediation analysis suggests that social risks represent the underlying mechanism behind the observed negative link between individual privacy risks and contact tracing apps' acceptance. Furthermore, we find a substantial intention–behavior gap. KW - digital contact tracing KW - privacy calculus KW - longitudinal study KW - privacy risks KW - surveillance KW - intention-behavior gap Y1 - 2022 U6 - https://doi.org/10.1016/j.ijinfomgt.2022.102473 SN - 0268-4012 SN - 1873-4707 VL - 64 SP - 1 EP - 16 PB - Elsevier CY - Kidlington ER - TY - JOUR A1 - Abramova, Olga A1 - Gladkaya, Margarita A1 - Krasnova, Hanna T1 - The differential effects of self-view in virtual meetings when speaking vs. listening JF - European journal of information systems N2 - With the surging reliance on videoconferencing tools, users may find themselves staring at their reflections for hours a day. We refer to this phenomenon as self-referential information (SRI) consumption and examine its consequences and the mechanism behind them. Building on self-awareness research and the strength model of self-control, we argue that SRI consumption heightens the state of self-awareness and thereby depletes participants’ mental resources, eventually undermining virtual meeting (VM) outcomes. Our findings from a European employee sample revealed contrary effects of SRI consumption across speaker vs listener roles. Engagement with self-view is positively associated with self-awareness, which, in turn, is negatively related to satisfaction with VM process, perceived productivity, and enjoyment. Looking at the self while listening to others exhibits adverse direct and indirect (via self-awareness) effects on VM outcomes. However, looking at the self when speaking exhibits positive direct effects on satisfaction with VM process and enjoyment. KW - self-view,virtual meetings KW - self-awarenesssender-receiver framework zoom KW - sender-receiver framework KW - Zoom Y1 - 2024 U6 - https://doi.org/10.1080/0960085X.2024.2325350 SN - 0960-085X SN - 1476-9344 SP - 1 EP - 19 PB - Taylor & Francis CY - London ER - TY - JOUR A1 - Hagemann, Linus A1 - Abramova, Olga T1 - Emotions and information diffusion on social media BT - a replication in the context of political communication on Twitter JF - AIS transactions on replication research N2 - 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. KW - Twitter KW - information diffusion KW - sentiment KW - elections Y1 - 2023 U6 - https://doi.org/10.17705/1atrr.00079 SN - 2473-3458 VL - 9 IS - 1 SP - 1 EP - 19 PB - AIS CY - Atlanta ER - TY - GEN A1 - Abramova, Olga T1 - No matter what the name, we're all the same? BT - examining ethnic online discrimination in ridesharing marketplaces T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - Sharing marketplaces emerged as the new Holy Grail of value creation by enabling exchanges between strangers. Identity reveal, encouraged by platforms, cuts both ways: While inducing pre-transaction confidence, it is suspected of backfiring on the information senders with its discriminative potential. This study employs a discrete choice experiment to explore the role of names as signifiers of discriminative peculiarities and the importance of accompanying cues in peer choices of a ridesharing offer. We quantify users' preferences for quality signals in monetary terms and evidence comparative disadvantage of Middle Eastern descent male names for drivers and co-travelers. It translates into a lower willingness to accept and pay for an offer. Market simulations confirm the robustness of the findings. Further, we discover that females are choosier and include more signifiers of involuntary personal attributes in their decision-making. Price discounts and positive information only partly compensate for the initial disadvantage, and identity concealment is perceived negatively. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 171 KW - sharing economy KW - discrimination KW - racism KW - discrete choice experiment KW - stated preferences KW - social inclusion Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-600641 SN - 1867-5808 ER - TY - CHAP A1 - Abramova, Olga A1 - Batzel, Katharina A1 - Modesti, Daniela T1 - Coping and regulatory responses on social media during health crisis BT - a large-scale analysis T2 - Proceedings of the 55th Hawaii International Conference on System Sciences N2 - During a crisis event, social media enables two-way communication and many-to-many information broadcasting, browsing others’ posts, publishing own content, and public commenting. These records can deliver valuable insights to approach problematic situations effectively. Our study explores how social media communication can be analyzed to understand the responses to health crises better. Results based on nearly 800 K tweets indicate that the coping and regulation foci framework holds good explanatory power, with four clusters salient in public reactions: 1) “Understanding” (problem-promotion); 2) “Action planning” (problem-prevention); 3) “Hope” (emotion-promotion) and 4) “Reassurance” (emotion-prevention). Second, the inter-temporal analysis shows high volatility of topic proportions and a shift from self-centered to community-centered topics during the course of the event. The insights are beneficial for research on crisis management and practicians who are interested in large-scale monitoring of their audience for well-informed decision-making. KW - Digital-Enabled Human-Information Interaction KW - big data KW - data mining KW - health crisis KW - social media Y1 - 2022 SN - 978-0-9981331-5-7 PB - HICSS Conference Office University of Hawaii at Manoa CY - Honolulu ER - TY - CHAP A1 - Hagemann, Linus A1 - Abramova, Olga T1 - Crafting audience engagement in social media conversations BT - evidence from the U.S. 2020 presidential elections T2 - Proceedings of the 55th Hawaii International Conference on System Sciences N2 - 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. KW - mediated conversation KW - big data KW - engagement KW - sentiment analysis KW - social media Y1 - 2022 SN - 978-0-9981331-5-7 SP - 3222 EP - 3231 PB - HICSS Conference Office University of Hawaii at Manoa CY - Honolulu ER - TY - CHAP A1 - Abramova, Olga T1 - Does a smile open all doors? BT - understanding the impact of appearance disclosure on accommodation sharing platforms T2 - Proceedings of the 53rd Hawaii International Conference on System Sciences N2 - 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. KW - The Sharing Economy KW - airbnb KW - online photographs KW - self-disclosure KW - sharing economy KW - social attraction Y1 - 2020 SN - 978-0-9981331-3-3 SP - 831 EP - 840 PB - HICSS Conference Office University of Hawaii at Manoa CY - Honolulu ER -