OSD2F: An Open-Source Data Donation Framework

The digital traces that people leave through their use of various online platforms provide tremendous opportunities for studying human behavior. However, the collection of these data is hampered by legal, ethical, and technical challenges. We present a framework and tool for collecting these data through a data donation platform where consenting participants can securely submit their digital traces. This approach leverages recent developments in data rights that have given people more control over their own data, such as legislation that now mandates companies to make digital trace data available on request in a machine-readable format. By transparently requesting access to specific parts of this data for clearly communicated academic purposes, the data ownership and privacy of participants is respected, and researchers are less dependent on commercial organizations that store this data in proprietary archives. In this paper we outline the general design principles, the current state of the tool, and future development goals

3bij3 – Developing a framework for researching recommender systems and their effects

Today’s online news environment is increasingly characterized by personalized news selections, relying on algorithmic solutions for extracting relevant articles and composing an individual’s news diet. Yet, the impact of such recommendation algorithms on how we consume and perceive news is still understudied. We therefore developed one of the first software solutions to conduct studies on effects of news recommender systems in a realistic setting. The web app of our framework (called 3bij3) displays real-time news articles selected by different mechanisms. 3bij3 can be used to conduct large-scale field experiments, in which participants’ use of the site can be tracked over extended periods of time. Compared to previous work, 3bij3 gives researchers control over the recommendation system under study and creates a realistic environment for the participants. It integrates web scraping, different methods to compare and classify news articles, different recommender systems, a web interface for participants, gamification elements, and a user survey to enrich the behavioural measures obtained

Is this a click towards diversity? Explaining when and why news users make diverse choices

Modelling the different factors that lead people to choose news articles is one of the key challenges for understanding the diversity of news diets - as a news diet is the result of a series of decisions for certain articles over others, a sequence of choices that was made by the individual consumer. This study sheds light on the interplay between content-related (past behavior, habits, preferences) and situational factors (positioning, saturation, control). The latter could offer possibilities to promote more unexpected news encounters that diverge from past news consumption. To test this, a Python-based web application for interactively testing different forms of news personalization over time was used. 247 respondents used the system over a two-week period, in total making almost 23,000 choices. Our results show that: (1) Selections are influenced by a strong positioning effect that follows a reading pattern (left-right, up-down). This effect is stable across devices, topics, and preferences. (2) How much control people are given influences the length and the amount of different sessions (personalization leads to fewer and shorter sessions). (3) With high control, the diversity of preferences influenced the diversity of selected news more, possibly widening gaps between diversity-seeking and -averse users. (4) How often a topic was chosen in the last hour negatively impacts whether it gets chosen again, showing saturation effects. (5) Clicks on sports and economic articles can be explained by preferences, but not past behavior; for political news the opposite is found. (6) There is no significant correlation between the actual diversity (presented or selected topics) and the topic diversity perceived by the users - in spite of clear differences in actual diversity between the groups. From this we can conclude the importance of situational factors in modelling news selection and their potential to narrow or widen the diversity corridor. In sum, our results contribute to a better understanding of the interaction of news recommender systems and humans and how this shapes which news articles get chosen

Subclinical femoral neuropathy after anterior cruciate ligament reconstruction

Background and aim of the study: Patients with anterior cruciate ligament (ACL) reconstruction and femoral catheter analgesia may develop quadriceps amyotrophy. We aimed to determine whether this amyotrophy might be related to a femoral neuropathy. Material and method: After Ethical Committee approval and patients' written informed consent, 17 patients ASA I and II scheduled to undergo ACL reconstruction were recruited. An electromyography (EMG) was performed before the operation in order to exclude a femoral neuropathy. A femoral nerve catheter was inserted before the surgery with the aid of a nerve stimulator, and 20 ml of 0.5% ropivacaine was injected. The operation was done under spinal or general anaesthesia. Postoperative analgesia was provided with 0.2% ropivacaine for 72 hours, in association with oxycodone, paracetamol and ibuprofen. A second EMG was performed 4 weeks after the ACL repair. A femoral neuropathy was defined as a reduction of the surface of the motor response of more than 20%, compared to the first EMG. A third EMG was performed at 6 months if a neuropathy was present. Results: Mean age of this group of patients was 27 years old (range 18-38 y.). Among the 17 patients, 4 developed a transient femoral neuropathy (incidence of 24%) without clinical complain. Conclusion: In this study, the incidence of subclinical femoral neuropathy after ACL reconstruction is high. This lesion may be caused by the femoral catheter (mechanical damage, toxicity of local anaesthesia) or by the Tourniquet. Further studies are needed to investigate the incidence of subclinical neuropathy, according to the type of analgesia (epidural analgesia, PCA) and surgery

Reading news with a purpose: Explaining user profiles for self-actualization

Personalized content provided by recommender systems is an integral part of the current online news reading experience. However, news recommender systems are criticized for their 'black-box' approach to data collection and processing, and for their lack of explainability and transparency. This paper focuses on explaining user profiles constructed from aggregated reading behavior data, used to provide content-based recommendations. The paper makes a first step toward consolidating epistemic values of news providers and news readers. We present an evaluation of an explanation interface reflecting these values, and find that providing users with different goals for self-actualization (i.e., Broaden Horizons vs. Discover the Unexplored) influences their reading intentions for news recommendations