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Peter A. Gloor

Publications and source records attributed to Peter A. Gloor.

At least 19 recordsLinked to original sources
arXiv2025

Plant Bioelectric Early Warning Systems: A Five-Year Investigation into Human-Plant Electromagnetic Communication

We present a comprehensive investigation into plant bioelectric responses to human presence and emotional states, building on five years of systematic research. Using custom-built plant sensors and machine learning classification, we demonstrate that plants generate distinct bioelectric signals correlating with human proximity, emotional states, and physiological conditions. A deep learning model based on ResNet50 architecture achieved 97% accuracy in classifying human emotional states through plant voltage spectrograms, while control models with shuffled labels achieved only 30% accuracy. This study synthesizes findings from multiple experiments spanning 2020-2025, including individual recognition (66% accuracy), eurythmic gesture detection, stress prediction, and responses to human voice and movement. We propose that these phenomena represent evolved anti-herbivory early warning systems, where plants detect approaching animals through bioelectric field changes before physical contact. Our results challenge conventional understanding of plant sensory capabilities and suggest practical applications in agriculture, healthcare, and human-plant interaction research.

q-bio.OT↗
arXiv2022

Emotion Recognition in Horses with Convolutional Neural Networks

Creating intelligent systems capable of recognizing emotions is a difficult task, especially when looking at emotions in animals. This paper describes the process of designing a "proof of concept" system to recognize emotions in horses. This system is formed by two elements, a detector and a model. The detector is a fast region-based convolutional neural network that detects horses in an image. The model is a convolutional neural network that predicts the emotions of those horses. These two elements were trained with multiple images of horses until they achieved high accuracy in their tasks. In total, 400 images of horses were collected and labeled to train both the detector and the model while 40 were used to test the system. Once the two components were validated, they were combined into a testable system that would detect equine emotions based on established behavioral ethograms indicating emotional affect through head, neck, ear, muzzle and eye position. The system showed an accuracy of 80% on the validation set and 65% on the test set, demonstrating that it is possible to predict emotions in animals using autonomous intelligent systems. Such a system has multiple applications including further studies in the growing field of animal emotions as well as in the veterinary field to determine the physical welfare of horses or other livestock.

cs.CV↗
arXiv2021

What Makes a Message Persuasive? Identifying Adaptations Towards Persuasiveness in Nine Exploratory Case Studies

The ability to persuade others is critical to professional and personal success. However, crafting persuasive messages is demanding and poses various challenges. We conducted nine exploratory case studies to identify adaptations that professional and non-professional writers make in written scenarios to increase their subjective persuasiveness. Furthermore, we identified challenges that those writers faced and identified strategies to resolve them with persuasive natural language generation, i.e., artificial intelligence. Our findings show that humans can achieve high degrees of persuasiveness (more so for professional-level writers), and artificial intelligence can complement them to achieve increased celerity and alignment in the process.

cs.CL↗
arXiv2021

Predicting the future success of scientific publications through social network and semantic analysis

Citations acknowledge the impact a scientific publication has on subsequent work. At the same time, deciding how and when to cite a paper, is also heavily influenced by social factors. In this work, we conduct an empirical analysis based on a dataset of 2010-2012 global publications in chemical engineering. We use social network analysis and text mining to measure publication attributes and understand which variables can better help predicting their future success. Controlling for intrinsic quality of a publication and for the number of authors in the byline, we are able to predict scholarly impact of a paper in terms of citations received six years after publication with almost 80 percent accuracy. Results suggest that, all other things being equal, it is better to co-publish with rotating co-authors and write the papers' abstract using more positive words, and a more complex, thus more informative, language. Publications that result from the collaboration of different social groups also attract more citations.

cs.DL↗
arXiv2021

Persuasive Natural Language Generation -- A Literature Review

This literature review focuses on the use of Natural Language Generation (NLG) to automatically detect and generate persuasive texts. Extending previous research on automatic identification of persuasion in text, we concentrate on generative aspects through conceptualizing determinants of persuasion in five business-focused categories: benevolence, linguistic appropriacy, logical argumentation, trustworthiness, tools and datasets. These allow NLG to increase an existing message's persuasiveness. Previous research illustrates key aspects in each of the above mentioned five categories. A research agenda to further study persuasive NLG is developed. The review includes analysis of seventy-seven articles, outlining the existing body of knowledge and showing the steady progress in this research field.

cs.CL↗
arXiv2020

Eurythmic Dancing with Plants -- Measuring Plant Response to Human Body Movement in an Anthroposophic Environment

This paper describes three experiments measuring interaction of humans with garden plants. In particular, body movement of a human conducting eurythmic dances near the plants (beetroots, tomatoes, lettuce) is correlated with the action potential measured by a plant SpikerBox, a device measuring the electrical activity of plants, and the leaf movement of the plant, tracked with a camera. The first experiment shows that our measurement system captures external stimuli identically for different plants, validating the measurement system. The second experiment illustrates that the plants' response is correlated to the movements of the dancer. The third experiment indicates that plants that have been exposed for multiple weeks to eurythmic dancing might respond differently to plants which are exposed for the first time to eurythmic dancing.

eess.SP↗
arXiv2020

Recognizing Individuals and Their Emotions Using Plants as Bio-Sensors through Electro-static Discharge

By measuring the electrostatic discharge of human bodies together with Mimosa Pudica and other plants in response to the human movement, we have been able to recognize (a) individuals based on their distinctive pattern of body movements with 66% accuracy as well as (b) positive or negative mood based on their gait characteristics with 85% accuracy. We use the Plant SpikerBox, a device that measures the electrical action potential while also measuring the electrostatic discharge between the electrode on the leaves of a plant and the capacitively coupled human body.

eess.SP↗
arXiv2017

"Making you happy makes me happy" -- Measuring Individual Mood with Smartwatches

We introduce a system to measure individual happiness based on interpreting body sensors on smartwatches. In our prototype system we use a Pebble smartwatch to track activity, heartrate, light level, and GPS coordinates, and extend it with external information such as weather data, humidity, and day of the week. Training our machine learning-based mood prediction system using random forests with data manually entered into the smartwatch, we achieve prediction accuracy of up to 94%. We find that besides body signals, the weather data exerts a strong influence on mood. In addition our system also allows us to identify friends who are indicators of our positive or negative mood.

cs.HC↗
arXiv2015

Cultural Anthropology through the Lens of Wikipedia: Historical Leader Networks, Gender Bias, and News-based Sentiment

In this paper we study the differences in historical World View between Western and Eastern cultures, represented through the English, the Chinese, Japanese, and German Wikipedia. In particular, we analyze the historical networks of the World's leaders since the beginning of written history, comparing them in the different Wikipedias and assessing cultural chauvinism. We also identify the most influential female leaders of all times in the English, German, Spanish, and Portuguese Wikipedia. As an additional lens into the soul of a culture we compare top terms, sentiment, emotionality, and complexity of the English, Portuguese, Spanish, and German Wikinews.

cs.CY↗
arXiv2015

Comparing Online Community Structure of Patients of Chronic Diseases

In this paper we compare the social network structure of people talking about Crohn's disease, Cystic Fibrosis, and Type 1 diabetes on Facebook and Twitter. We find that the Crohn's community's contributors are most emotional on Facebook and Twitter and most negative on Twitter, while the T1D community's communication network structure is most cohesive.

cs.SI↗
arXiv2015

Proceedings of the 5th International Conference on Collaborative Innovation Networks COINs15, Tokyo, Japan March 12-14, 2015

The 5th annual international conference on Collaborative Innovation Networks Conference (COINS) takes place at Keio University from March 12 to 14, 2015. COINS15 brings together practitioners, researchers and students of the emerging science of collaboration to share their work, learn from each other, and get inspired through creative new ideas. Where science, design, business and art meet, COINS15 looks at the emerging forces behind the phenomena of open-source, creative, entrepreneurial and social movements. Through interactive workshops, professional presentations, and fascinating keynotes, COINS15 combines a wide range of interdisciplinary fields such as social network analysis, group dynamics, design and visualization, information systems, collective action and the psychology and sociality of collaboration.

cs.SI↗
arXiv2014

Measuring Team Creativity Through Longitudinal Social Signals

Research into human dynamical systems has long sought to identify robust signals for human behavior. We have discovered a series of social network-based indicators that are reliable predictors of team creativity and collaborative innovation. We extract these signals from electronic records of interpersonal interactions, including e-mail, and face-to-face interaction measured via sociometric badges. The first of these signals is Rotating Leadership, measuring the degree to which, over time, actors in a team vary in how central they are to team's communication network's structure. The second is Rotating Contribution, which measures the degree to which, over time, actors in a team vary in the ratio of communications they distribute versus receive. The third is Prompt Response Time, which measures, over time, the responsiveness of actors to one another's communications. Finally, we demonstrate the predictive utility of these signals in a variety of contexts, showing them to be robust to various methods of evaluating innovation.

cs.SI↗
arXiv2013

COINs change leaders - Lessons Learned from a Distributed Course

In this paper we analyze the communication network of 50 students from five universities in three countries participating in a joint course on Collaborative Innovation Networks (COINs). Students formed ten teams. Interaction variables calculated from the e-mail archive of individual team members predict the level of creativity of the team. Oscillating leadership, where members switch between central and peripheral roles is the best predictor of creativity, it is complemented by the variance in the amount of sending or receiving information, and by answering quickly, and positive language. We verify our automatically generated creativity metrics with interviews.

cs.CY↗
arXiv2013

Coolhunting for the World's Thought Leaders

Which thinkers are we guided by? A novel "Thought Leader Map" shows the select group of people with real influence who are setting the trends in the market for ideas. The influencers in philosophy, sociology, economics, and the "hard sciences" have been identified by a Delphi process, asking 50 thought leaders to name their peers. The importance of the influencers is calculated by constructing a co-occurrence network in the Blogosphere. Our main insight is that the era of the great authorities seems to be over. Major thought leaders are rare - the picture is composed of many specialists.

cs.SI↗
arXiv2013

Increasing Knowledge Worker Efficiency through a "Virtual Mirror" of the Social Network

In this paper we introduce a case study describing the combination of manual survey-based and e-mail-based social network analysis. The goal of the project was to increase collaboration efficiency in a team of consultants of a major high tech manufacturer. By analyzing the social network of a team of 42 consultants and comparing it with their utilization as the dependent variable, their efficiency in working together was improved in various way by bridging structure holes and eliminating bottlenecks, reducing stress for overburdened individuals, connecting isolated individuals and identifying the best network structures for high utilization and increased job satisfaction.

cs.SI↗
arXiv2013

Predicting Client Satisfaction through (E-Mail) Network Analysis: The Communication Score Card

This study seeks to better understand the network characteristics of client support teams by analyzing the teams' e-mail communication networks and comparing it to client organization's satisfaction. In collaboration with a large service provider we studied the impact of network properties on the satisfaction of client organizations. In particular, we found that social network metrics correlate with client satisfaction as measured by Net Promoter Score (NPS). A Communication Score Card is suggested as a dashboard to continuously measure client satisfaction, illustrating that data-driven analysis might help improving service providers' service quality management.

cs.SI↗
arXiv2013

WikiPulse - A News-Portal Based on Wikipedia

More and more user-generated content is complementing conventional journalism. While we don't think that CNN or New York Times and its professional journalists will disappear anytime soon, formidable competition is emerging through humble Wikipedia editors. In earlier work (Becker 2012), we found that entertainment and sports news appeared on average about two hours earlier on Wikipedia than on CNN and Reuters online. In this project we build a news-reader that automatically identifies late-breaking news among the most recent Wikipedia articles and then displays it on a dedicated Web site.

cs.IR↗