Face-to-Face and Email Negotiations: A Comparison of Emotions, Perceptions and Outcomes

The purpose of this research was to conduct and exploratory study comparing email to face-to-face negotiations primarily focusing on emotions across the two negotation environments. We used a bargaining task with a negative bargaining zone for the negotiation and pre- and post-negotiations surveys to measure motivations, emotions, and perceptions. We found that email dyads had less pro-social concerns, were less likely to reach agreement, less satisfied with the quality of the interaction during the negotiation, reported less rapport and rated future trust in their partner significantly lower than face-to-face dyads. Those negotiating face-to-face ratede their own emotions during the negotiations and those of the other party significantly higher than those negotiating over email. However, accuracy in emotion percepition was greater in the email dyads. Finally, our research shows that accuracy in perceiving negative emotions is a significant predictor of settlement, regardless of negotiation environment. Limitations an implications for future research directions are discussed

A deep dive into distributive concession making and the likelihood of impasses in negotiations

Negotiation impasses can have severe negative consequences, but only little research attention has been devoted to investigating their causes. Studies on distributive concession making (i.e., high demands and low concessions) as a cause of impasses were inconclusive due to low sample sizes and methodological choices. Moreover, distributive concession making entails two hitherto fully entangled properties: reduction of conceded value and violation of the reciprocity norm. In our experiment, participants negotiated with a confederate who administered different concession patterns that allowed us to disentangle these properties. We found unambiguous evidence that distributive concession making increases the likelihood of impasses. This effect was driven by the reduction of conceded value rather than the violation of the reciprocity norm. Confrontation with distributive concession making led participants to develop negative internal attributions and anger, which mediated the effect of distributive concession making on the impasse rate. Our study contributes to a better understanding of the causes and underlying mechanisms of negotiation impasses

Impact of Service Characteristics on Rational and Emotional Components of Information Systems Service Evaluations

Information systems (IS) research and practice have recognized the need to move the IS field to a more service oriented paradigm. This requires a good understanding of how IS services are evaluated and the factors that influence the perceptions of service performance. Measures of IS service quality have provided an insight into the rational/technical factors that influence the evaluation of IS services. Recently, the need for the investigation of additional factors that influence IS service evaluations has been recognized. One such factor that can influence the evaluation of an IS service is the emotional response that the IS service elicits in a recipient. Emotional responses play a major role in building attitudes, beliefs and behavioral intentions. However, IS service research has focused more on the rational aspects of these phenomena while largely ignoring the emotional aspects when explaining IS service evaluations. This research seeks to provide a better understanding of how individuals evaluate IS services by focusing on the salient characteristics of the IS service that can influence these evaluations. To achieve this, the research focuses on two research objectives: (1) to investigate the how the individual components of IS service evaluations – the emotional and rational evaluation components – impact various behaviors associated with the IS service and (2) to investigate how specific, theory driven service characteristics impact the emotional and relational components of IS service evaluation. A controlled experiment is used to investigate IS service evaluations and the characteristics of IS services that influence them. Results suggest that both emotional and rational components of IS service evaluations have significant impacts on behavioral intentions associated with the IS service. Furthermore, findings indicate that while the specificity of service output impacts both the emotional and rational evaluations of the IS service, the complexity of the service task only influences the emotional component by increasing the level of emotional evaluations associated with the service. Proximity between service provider and service recipient was found to have no significant impact on the emotional evaluation of the service

Everything You Never Wanted to Know about Trolls:An Interdisplinary Exploration of the Who's, What's, and Why's of Trolling in Online Games

Summary Within the world of online gaming, trolling has become a regular menace. While gamers try to connect and socialize with one another, or even simply play the game, there are other gamers – trolls – on the prowl for an entirely different kind of good time, one in which they are enjoying themselves at the expense of everyone else (Chapters 2 and 3). Although trolling is common, and mass-media has latched onto it as a hot topic, it is only recently that the academic community has begun to take a serious look at how trolling occurs in and affects the gaming community at large. However, a lot of this literature is either descriptive in nature (see Thacker & Griffiths, 2012), or jumps ahead to prevention (see Cheng et al., 2017) without taking a deeper look at more than a single underlying motivation at a time. In short, there is a complex and prolific phenomenon happening online, but the research on it is only emerging. This dissertation’s goal is to take a deeper look at trolling as a phenomenon, beyond what has been done so far. More specifically, I aim to figure out a) what trolling is, b) why people do it, and c) who helps and who hinders trolling in online games. To do this, I took four different perspectives: the troll’s (Chapter 2), the researcher’s (Chapter 3), the victim’s (Chapter 4), and the bystander’s (Chapter 5). The purpose of Chapter 2 is to give the troll’s perspective on trolling, something that researchers had yet to do at the time. To do this, I interviewed 22 people who said that they had a history of trolling in online games. More specifically, I asked them about times they witnessed, were victims of, or perpetrated trolling, as well as what they thought about how the gaming community dealt with and felt about trolls and trolling. My goal with these interviews was threefold: I wanted to figure out a) what trolls consider trolling, b) what motivates them to do it, and c) the role of everyone else in game when it comes to encouraging or discouraging more trolling. What I found was that although trolling was almost universally considered a negative part of online gaming culture, and all the trolls in our group of participants started as victims of trolls before becoming trolls themselves, the online community neither encourages nor discourages it, making it an asocial activity. The next chapter allowed me to look at an archive of trolling incidents to find patterns in the way that different people involved in real-life trolling incidents communicate with one another. This public online archive consisted of 10,000 reported incidents of trolling in the popular online game League of Legends, and it included game data like player statistics, as well as everything all the players involved said during the game. Once the data was properly cleaned and prepared, myself and my co-author, Dr. Rianne Conijn, analysed the chat logs in two different ways: structural topic modelling (STM), and a traditional dictionary-based content analysis. In this way, we were able to see what characterized all the different actors – the troll, their victim(s), and the bystanders – and what was similar when it came to their messages. All this information was then compared to what existed already in literature used to describe trolls and trolling and complement what I had learned about trolls from Chapter 2. The key finding was that trolls and their teammates actually share a lot of the negative speech patterns (e.g., profanity, negative emotional content) normally associated with only trolls. Practically, this means that we have to be extremely careful as researchers when labelling trolls for the purpose of study, as we could very easily be falsely labelling victims. After speaking to trolls and looking at trolling interactions broadly, Chapter 4 focuses intently on the victim and their personal experience in a trolling simulation, taking into account their cultural background and values. It is also the first study to directly compare and contrast two different types of trolling: verbal (flaming) and behavioural (ostracism). They are both really common online occurrences, so the participants could easily relate, but they are extremely different in how they are executed, with flaming being vicious insults and ostracism being totally ignoring a person. Our participants were either Dutch, Pakistani, or Taiwanese, so that we could also look at how people from vastly different cultural backgrounds would react to – behaviourally and emotionally – the different kinds of trolling in the study. We simulated a trolling experience by putting our participants in a virtual game of catch with two computerized co-players, who they were led to believe were real people of either the same nationality or a minority member (e.g., a Moroccan immigrant in the Netherlands), who I had programmed to either troll them or silently watch the trolling happen. We found that there are indeed cultural differences when it comes to reactions, as well as differences between reactions to the two trolling types, but the core take-away is that future trolling interventions have to take into account the cultures of the target population as well as the specific type of trolling they are trying to fix or prevent in order to be effective. In the penultimate chapter, I shift the focus one last time to bystanders by putting participants in a game of League of Legends with two confederates who would troll one another throughout the game. This study’s goal was to see what motivated gamers to report trolls to an authority figure (the game developer) using the game’s built-in reporting functions, as the results of Chapter 2’s study suggested that this was an effective trolling deterrent. It is also, according to the results of the same study, the least-used recourse by bystanders faced with trolls in the proverbial wild. We found that how warm and friendly the troll was perceived to be and how competent the victim was perceived to be were what determined whether the participant reported our fake troll or not. A more competent victim and a less warm troll lead to more reports. To conclude, there is still a lot more to learn about trolls and trolling, but the field is farther along now than when this project started in 2015. There is a broad definition developed that encompasses most of the descriptive literature on trolling in games thus far. We also now know that there is the indication of a trolling cycle that requires further exploration. This is particularly important to know when it comes to the world of game development, as knowing the cycle exists allows for multiple points of intervention in order to protect their customers. Finally, this dissertation has shown the complexity of not just trolls – who are often portrayed in the media as one-dimensional antagonists – but also of everyone else involved in trolling interactions. Trolls, victims, and bystanders are all multi-faceted humans, and trolling, like all interactions, is an intricate social dance that deserves to be studied in even further depth in the future than what I have done here

Communicating Climate Change In Internet Discussion Fora: Processes and Implications

Communicating climate change issues in the Internet era requires new strategies that incorporate online communication. The rapid growth of new media and widespread use of the internet has marked everyday lifestyles in modern society. Information on a wide range of social issues, including climate change, is disseminated and debated through online discussions in internet fora. In this research, communication on internet fora and other potential forms of online social interaction are explored, to identify ways to enhance climate change communication on the Internet. The thesis raises three research questions to explore the communication context of internet fora discussion, namely: what are characteristics of the communication process on internet fora? Who is involved in the communication process? What influences do these online communication activities have on users’ everyday activities? The research applies a mixed-methods approach of analysing the usage of Internet fora and the contents of fora communication activities to explore these questions. This includes qualitative reviews of topic-thread discussions to reveal users’ roles in discussions, as well as surveys of fora users. It is argued that with increasing levels of interaction among communicators (people who post or reply to articles in order to express or respond ideas) on internet fora, these communicators are mobilised to join the online discussion process, competing for opinion leadership. The online discussions further contribute to the formation of opinions on climate change, as climate change and related issues are discussed The thesis thereby aims to contribute to the development of effective approaches for opinion formation and climate change communication online, and to encourage individuals to discuss changing behaviour patterns and public engagement of greenhouse gas reduction actions

Managing and imagining migration: The role of Facebook groups in the lives of “new” Italian migrants in Australia

This thesis explores the role that Facebook groups play in the lives of the so called “new” wave of Italian migrants in Australia both pre- and post-migration. Over the last decade, especially since the 2008 Global Financial Crisis, large numbers of young Ita¬lians have been arriving in Australia, however little is known about their migratory experiences. Similarly, while scholars in the field of technology and migration have shown that online communication can facilitate the process of migration, it is still unclear whether it can also influence migrants’ expectations before they have even left their home countries. Therefore, in order to elucidate whether – ¬and how – Facebook groups shape pre-migration expectations and subsequent post-migration experiences, two data sources have been employed: a thematic analysis of the wallposts made to three public, user-created Facebook groups dedicated to “new” Italians in Australia, and in-depth interviews with members of these groups. Findings show that these Facebook groups are online communities where “new” Italian migrants come together at various stages of the migration process in order to prepare for, manage and imagine the experience of migrating to Australia. By joining Facebook groups prior to migrating, “new” Italian migrants can gain access to social support, relevant, practical information, and insider knowledge about how to prepare for everyday life in Australia and what to expect upon arrival. Likewise, belonging to Facebook groups can help “new” Italian migrants manage their post-migration experiences by providing them with opportunities for employment and socialisation, and for regaining social capital. Overall, the first-hand migration stories and images posted by those already in Australia construct a hyper-reality, that is, a space or window for pre-migrants to imagine what it is like to be an Italian migrant in Australia today and, in turn, shape realistic expectation

Sentiment analysis in electronic negotiations

The thesis analyzes the applicability of methods of Sentiment Analysis and Predictive Analytics on textual communication in electronic negotiation transcripts. In particular, the thesis focuses on examining whether an automatic classifier can predict the outcome of ongoing, asynchronous electronic negotiations with sufficient accuracy. When combined with influencing factors leading to the specific classification decision, such a classification model could be incorporated into a Negotiation Support System in order to proactively intervene in ongoing negotiations it judges as likely to fail and then to give advice to the negotiators to prevent negotiation failure. To achieve this goal, an existing data set of electronic negotiations was used in a first study to create a Sentiment Lexicon, which tracks verbal indicators for utterances of positive and, respectively, negative polarity. This lexicon was subsequently combined with a simplified, feature-based representation of electronic negotiation transcripts which was then used as training data for various machine learning classifiers in order to let them determine the outcome of the negotiations based on the transcripts in a second study. Here, complete negotiation transcripts were classified as well as partial transcrips in order to assess classification quality in ongoing negotiations. The third study of the thesis sought to refine the classification model with respect to sentence-based granularity. To this end, human coders were classifying negotiation sentences regarding their subjectivity and polarity. The results of this content analysis approach were then used to train sentence-level subjectivity and polarity classifiers. The fourth and final study analyzed different aggregation methods for these sentence-level classification results in order to support the classifiers on negotiation granularity. Different aggregation and classification models were discussed, applied to the negotiation data and subsequently evaluated. The results of the studies show that it is possible to a certain degree to use a sentiment-based representation of negotiation data to automatically determine negotiation outcomes. In combination with the sentence-based classification models, negotiation classification quality increased further. However, this improvement was only found to be significant for complete negotiation transcripts. If only partial transcripts are used specifically to simulate an ongoing negotiation scenario the models tend to behave more erratic and classifcation quality depletes. This result yields the assumption that polarized utterances (positive as well as negative) only carry unequivocal information (with respect to the outcome) towards the end of the negotiation. During the negotiation, the influence of these utterances becomes more ambiguous, hence decreasing classification accuracy on models using a representation based on sentiments. Regarding the original goal of the thesis, which is to provide a basic means to support ongoing negotiations, this means that supporting mechanisms employed by a Negotiation Support System should focus on moderation techniques and resolving of potentially conflicting situations. Approaches that could be used to employ further conflict diagnosis in interaction with the negotiators are given in the final chapter of the thesis, as well as a discussion of potential recommendations and advice the system could give and lastly, approaches to visualize the classification data to the negotiators.Im Rahmen der Arbeit wurde die Anwendbarkeit von Methoden der Sentiment Analysis und Predictive Analytics auf textuelle Kommunikation in elektronischen Verhandlungen untersucht. Insbesondere sollte ermittelt werden, ob ein automatisiertes Klassifikationsverfahren in laufenden, asynchron geführten elektronischen Verhandlungen mit hinreichender Genauigkeit den Verhandlungsausgang vorhersagen kann. Eine solche Klassifikation, kombiniert mit den Einflussfaktoren, die zu der entsprechenden Klassifikation geführt haben, könnte dann im Rahmen eines Verhandlungsunterstützungssystems genutzt werden, um proaktiv in die Verhandlung einzugreifen um ggf. einen erfolglosen Ausgang der Verhandlung zu verhindern. Basierend auf einem existierenden Datensatz elektronischer Verhandlungen wurde hierzu in einer ersten Studie ein sogenanntes Sentiment-Lexikon erstellt, welches Indikatoren für positive bzw. negative Äußerungen sammelt. Dieses Lexikon sowie eine vereinfachte, Feature-basierte Repräsentation der Verhandlungsdaten diente in einer zweiten Studie als Grundlage, um maschinelle Lernverfahren zu trainieren, die das Resultat der Verhandlung basierend auf den textuellen Daten ermitteln sollten. Die Verfahren wurden sowohl auf vollständigen als auch auf partiellen Verhandlungstranskripten angewendet, um die Klassifikationsqualität in laufenden Verhandlungen bestimmen zu können. Im Rahmen einer dritten Studie wurde eine Verfeinerung des Lernverfahrens auf der Granularität einzelner Sätze durchgeführt. Hierzu wurden Sätze aus Verhandlungen von menschlichen Codern hinsichtlich Subjektivität vs. Objektivität und Polarität (positiv vs. negativ) bewertet. Die Resultate dieser Inhaltsanalyse dienten als Input für maschinelle Lernverfahren, die automatisiert Sätze bezüglich der beiden genannten Dimensionen klassifizieren. In einer finalen Integrationsstudie wurden die Ergebnisse der Klassifikationsverfahren auf Satz-Ebene aggregiert und verwendet um die Klassifikation auf Verhandlungsebene zu unterstützen. Hierbei wurden verschiedene Alternativen zur Aggregation durchgeführt und bewertet. Die Resultate der einzelnen Studien zeigen, dass es mit Abstrichen möglich ist, mit einer Sentiment-basierten Repräsentation von Verhandlungsdaten das Ergebnis einer Verhandlung vorherzusagen. Insbesondere wenn die Klassifikationsmodelle mit feingranularen Informationen angereichert werden, steigt die Qualität der Vorhersage für einzelne Modelle weiter signifikant an. Dies trifft jedoch nur auf Transkripte vollständiger Verhandlungen zu werden nur partielle Transkripte verwendet im Sinne einer möglichst frühzeitigen Vorhersage des Resultats verhalten sich die Modelle erratischer und die Genauigkeit degeneriert. Die mit diesem Resultat verbundene Annahme ist, dass polarisierte Äußerungen (positiv wie negativ) in erster Linie gegen Ende der Verhandlung eindeutige Informationen liefern insbesondere Sentiments in der Mitte der Transkripte scheinen der Klassifikationsqualität eher abträglich. Für konkrete proaktive Unterstützungsmaßnahmen, die ein Verhandlungsunterstützungssystem zu diesem Zeitpunkt ergreifen kann bedeutet dies in erster Linie, dass diese Maßnahmen im Falle dass die Verhandlung zu scheitern droht auf eine Moderation und Auflösung eventueller Konfliktsituationen abzielen sollten. Hierzu werden im Rahmen des Ausblicks in der Thesis ausführlich denkbare Ansätze zur weiteren Konfliktdiagnose in Interaktion mit den Nutzern, Ansätze für Empfehlungen und Ratschlägen, die das System geben kann, sowie Visualisierungsansätze diskutiert