A Look Through a Broken Window: The Relationship Between Disorder and Toxicity on Social Networking Sites

Toxicity has increased on social networking sites (SNSs), sparking a debate on its underlying causes. While research readily explored eligible social factors, disorder induced by the very nature of SNSs has been neglected so far. The relationship between disorder and deviant behaviors could be revealed within the offline sphere. Incorporating the theoretical lens of the Broken Windows Theory, we propose that a similar mechanism is prevalent in the online context. To test the hypothesis that perceived disorder increases toxicity on SNSs, the study compares two subcommunities on Reddit dedicated to the same topic that differ in their perceived disorder. Sampling the toxicity scores via data collection and natural language processing yields the first evidence for our hypothesis. We further outline subsequent studies that aim to investigate further the phenomenon of how disorder-related factors contribute to toxic online environments

The Price of Privacy - An Evaluation of the Economic Value of Collecting Clickstream Data

The analysis of clickstream data facilitates the understanding and prediction of customer behavior in e-commerce. Companies can leverage such data to increase revenue. For customers and website users, on the other hand, the collection of behavioral data entails privacy invasion. The objective of the paper is to shed light on the trade-off between privacy and the business value of cus- tomer information. To that end, the authors review approaches to convert clickstream data into behavioral traits, which we call clickstream features, and propose a categorization of these features according to the potential threat they pose to user privacy. The authors then examine the extent to which different categories of clickstream features facilitate predictions of online user shopping pat- terns and approximate the marginal utility of using more privacy adverse information in behavioral prediction models. Thus, the paper links the literature on user privacy to that on e-commerce analytics and takes a step toward an economic analysis of privacy costs and benefits. In par- ticular, the results of empirical experimentation with large real-world e-commerce data suggest that the inclusion of short-term customer behavior based on session-related information leads to large gains in predictive accuracy and business performance, while storing and aggregating usage behavior over longer horizons has comparably less value

WHY PHUBBING IS TOXIC FOR YOUR RELATIONSHIP: UNDERSTANDING THE ROLE OF SMARTPHONE JEALOUSY AMONG “GENERATION Y” USERS

Coined as “phubbing”, excessive use of smartphones in the romantic context has been shown to rep-resent a barrier to meaningful communication, causing conflict, lowering relationship satisfaction, and undermining individual well-being. While these findings project a dire picture of the future of romance, the mechanisms behind the detrimental influence of partner phubbing on relationship-relevant markers are still little understood. Considering prior evidence that partner phubbing leads to the loss of exclusive attention towards the other party, we argue that these are rather the feelings of jealousy partner phubbing is triggering that are responsible for the negative relational outcomes. Based on the analysis of qualitative and quantitative responses from “generation Y” users, we find that partner phubbing is associated with heightened feelings of jealousy, which is inversely related to couple’s relational cohesion. Moreover, jealousy plays a mediating role in the relationship between partner’s smartphone use and relational cohesion, acting as a mechanism behind this undesirable link. Challenging the frequently promoted euphoria with regard to permanent “connectedness”, our study contributes to a growing body of IS research that addresses dark sides of information technolo-gy use and provides corresponding implications for IS practitioners

Privacy Policies and Users’ Trust: Does Readability Matter?

Over the years, a drastic increase in online information disclosure spurs a wave of concerns from multiple stakeholders. Among others, users resent the “behind the closed doors” processing of their personal data by companies. Privacy policies are supposed to inform users how their personal information is handled by a website. However, several studies have shown that users rarely read privacy policies for various reasons, not least because limitedly readable policy texts are difficult to understand. Based on our online survey with over 440 responses, we examine the objective and subjective readability of privacy policies and investigate their impact on users’ trust in five big Internet services. Our findings show the stronger a user believes in having understood the privacy policy, the higher he or she trusts a web site across all companies we studied. Our results call for making readability of privacy policies more accessible to an average reader

TWITTER AND THE POLITICAL LANDSCAPE – A GRAPH ANALYSIS OF GERMAN POLITICIANS

This paper examines the Twitter social graph of German politicians and political parties during a time period not potentially biased by nearby elections. Based on a data set of 1,719 politicians across the entire political spectrum of this important country in the EU, two graphs are constructed, which also reflect relationships within and between parties: the follower graph, consisting of all follower-followee relationships between German politicians, and the “mention graph”, which models direct references of politicians to their colleagues. Our main contributions are as follows: First, we analyse these graphs according to several statistics and graph metrics, characterizing political parties according to their collective participation in Twit-ter. We also investigate the openness for following ideas across political camps, resulting in the dis-covery of three distinct groups of political parties. We also find that membership in political parties itself explains only little of the variation in the formation of ties. There is also evidence that politicians with less activity exhibit a higher degree of openness than users with active engagement in tweets and discussions. This case study on social media adoption in politics leads to interesting insights into po-litical debate in the information society

Shopping Online – Determining Consumer Acceptance of Online Shops

After more than ten years of widespread use of e-commerce, there are still only a few models to specify the connectionbetween consumer acceptance and the characteristics of an online shop. In particular, the available literature does not provideany constructs to evaluate the most basic functionality of an online shop: its search features. In this paper we describe ashopping experiment to validate a model that includes consumer characteristics as well as consumers\u27 evaluations of a shop’ssearch features. Results demonstrate that (i) contrary to consumer research findings, only consumer involvement influencesthe consumers’ evaluation of the online shop, not the prior product knowledge; (ii) the relevance of search results and theevaluation of filtering mechanisms have a major impact on the perceived usefulness of the shop; and (iii) the ease of use ofthe shop does not affect perceived usefulness, as this relationship is fully mediated by the perceived costs of the informationsearch process

Men, Women, Microblogging: Where Do We Stand?

With millions of users worldwide, microblogging has developed into a powerful tool for interaction and information dissemination. While both men and women readily use this technology, there are significant differences in how they embrace it. Understanding these differences is important to ensure gender parity, provide advertisers with actionable insights on the marketing potential of both groups, and to inform current theories on how microblogging affordances shape gender roles. So far, existing research has not provided a unified framework for such analysis, with gender insights scattered across multiple studies. To fill this gap, our study conducts a comprehensive meta-review of existing research. We find that current discourse offers a solid body of knowledge on gender differences in adoption, shared content, stylistic presentation, and a rather convoluted picture of female and male interaction. Together, our structured findings offer a deeper insight into the underlying dynamics of gender differences in microblogging

Maximize What Matters: Predicting Customer Churn With Decision-Centric Ensemble Selection

Churn modeling is important to sustain profitable customer relationships in saturated consumer markets. A churn model predicts the likelihood of customer defection. This is important to target retention offers to the right customers and to use marketing resources efficiently. The prevailing approach toward churn model development, supervised learning, suffers an important limitation: it does not allow the marketing analyst to account for campaign planning objectives and constraints during model building. Our key proposition is that creating a churn model in awareness of actual business requirements increases the performance of the final model for marketing decision support. To demonstrate this, we propose a decision-centric framework to create churn models. We test our modeling framework on eight real-life churn data sets and find that it performs significantly better than state-of-the-art churn models. Further analysis suggests that this improvement comes directly from incorporating business objectives into model building, which confirms the effectiveness of the proposed framework. In particular, we estimate that our approach increases the per customer profits of retention campaigns by $.47 on average

The nature and persistence of the effects of posthypnotic suggestions on food preferences: The final report of an online study

The persistence of food preferences, which are crucial for diet-related decisions, is a significant obstacle to changing unhealthy eating behavior. To overcome this obstacle, the current study investigates whether posthypnotic suggestions (PHSs) can enhance food-related decisions by measuring food choices and subjective ratings. After assessing hypnotic susceptibility in Session 1, at the beginning of Session 2, a PHS was delivered aiming to increase the desirability of healthy food items (e.g., vegetables and fruit). After the termination of hypnosis, a set of two tasks was administrated twice, once when the PHS was activated and once deactivated in counterbalanced order. The task set consisted of rating 170 pictures of food items, followed by an online supermarket where participants were instructed to select enough food from the same item pool for a fictitious week of quarantine. After 1 week, Session 3 mimicked Session 2 without renewed hypnosis induction to assess the persistence of the PHS effects. The Bayesian hierarchical modeling results indicate that the PHS increased preferences and choices of healthy food items without altering the influence of preferences in choices. In contrast, for unhealthy food items, not only both preferences and choices were decreased due to the PHS, but also their relationship was modified. That is, although choices became negatively biased against unhealthy items, preferences played a more dominant role in unhealthy choices when the PHS was activated. Importantly, all effects persisted over 1 week, qualitatively and quantitatively. Our results indicate that although the PHS affected healthy choices through resolve, i.e., preferred more and chosen more, unhealthy items were probably chosen less impulsively through effortful suppression. Together, besides the translational importance of the current results for helping the obesity epidemic in modern societies, our results contribute theoretically to the understanding of hypnosis and food choices.Peer Reviewe