Top Comment or Flop Comment? Predicting and Explaining User Engagement in Online News Discussions

Comment sections below online news articles enjoy growing popularity among readers. However, the overwhelming number of comments makes it infeasible for the average news consumer to read all of them and hinders engaging discussions. Most platforms display comments in chronological order, which neglects that some of them are more relevant to users and are better conversation starters. In this paper, we systematically analyze user engagement in the form of the upvotes and replies that a comment receives. Based on comment texts, we train a model to distinguish comments that have either a high or low chance of receiving many upvotes and replies. Our evaluation on user comments from TheGuardian.com compares recurrent and convolutional neural network models, and a traditional feature-based classifier. Further, we investigate what makes some comments more engaging than others. To this end, we identify engagement triggers and arrange them in a taxonomy. Explanation methods for neural networks reveal which input words have the strongest influence on our model's predictions. In addition, we evaluate on a dataset of product reviews, which exhibit similar properties as user comments, such as featuring upvotes for helpfulness.Comment: Accepted at the International Conference on Web and Social Media (ICWSM 2020); 11 pages; code and data are available at https://hpi.de/naumann/projects/repeatability/text-mining.htm

Zielgruppenorientiertes Projektmanagement als Werkzeug der Öffentlichkeitsarbeit von öffentlichen Bibliotheken : Konzeption, Durchführung und Evaluation einer Veranstaltungswoche zum Thema Regenwald für Kinder in der Stadtbücherei Biberach/Riß

Die vorliegende Arbeit beschäftigt sich mit der theoretischen Planung und der praktischen Umsetzung einer Veranstaltungswoche für Kinder zum Thema Regenwald. Hintergrund dieses Projektes war die Erprobung meiner schulisch erworbenen Kenntnisse bezüglich Projektmanagement in der Praxis. Gleichzeitig erschien es mir wichtig zu zeigen, wie Bibliotheken auch kritische Themen für Kinder attraktiv und verständlich gestalten können. Zudem sollen die Möglichkeiten der Zusammenarbeit mit anderen städtischen und nichtstädtischen Einrichtungen verdeutlicht werden, auch wenn die Bereitschaft dazu bei unserem Projekt nicht immer vorhanden war. Im folgenden Text habe ich sowohl meine Überlegungen und meine Vorgehensweise als auch meine Erfahrungen festgehalten. Diese Arbeit soll auch von anderen Bibliotheken als Anreiz für die Gestaltung ähnlicher Veranstaltungen genutzt werden

On the use of language models and topic models in the web : new algorithms for filtering, classification, ranking, and recommendation

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ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data

RNA-binding proteins (RBPs) play an important role in RNA post-transcriptional regulation and recognize target RNAs via sequence-structure motifs. The extent to which RNA structure influences protein binding in the presence or absence of a sequence motif is still poorly understood. Existing RNA motif finders either take the structure of the RNA only partially into account, or employ models which are not directly interpretable as sequence-structure motifs. We developed ssHMM, an RNA motif finder based on a hidden Markov model (HMM) and Gibbs sampling which fully captures the relationship between RNA sequence and secondary structure preference of a given RBP. Compared to previous methods which output separate logos for sequence and structure, it directly produces a combined sequence-structure motif when trained on a large set of sequences. ssHMM’s model is visualized intuitively as a graph and facilitates biological interpretation. ssHMM can be used to find novel bona fide sequence-structure motifs of uncharacterized RBPs, such as the one presented here for the YY1 protein. ssHMM reaches a high motif recovery rate on synthetic data, it recovers known RBP motifs from CLIP-Seq data, and scales linearly on the input size, being considerably faster than MEMERIS and RNAcontext on large datasets while being on par with GraphProt. It is freely available on Github and as a Docker image

Non-myopic Sensor Path Planning for Emitter Localization with a UAV

This paper addresses the problem of localizing a stationary RF emitter with a mobile UAV, equipped with a single directional antenna. By rotating around its vertical axis, it determines a bearing towards the emitter. Our interest is in optimally selecting the measurement positions to achieve a fast localization. The majority of such systems described in the literature use greedy planning to select the next measurement position. This work experimentally tests an algorithm that performs a non-myopic planning until the final localization step. The algorithm is based on the policy rollout principle and showed good performance in previous simulative studies. It is adapted to match the needs of a real world setup and evaluated in flight trials. Adaptions include the avoidance of close range measurements to prevent inaccurate measurements at high elevation, and the filtering of poor measurements

Validation of Tagging Suggestion Models for a Hotel Ticketing Corpus

This paper investigates methods for the prediction of tags on a textual corpus that describes hotel staff inputs in a ticketing system. The aim is to improve the tagging process and find the most suitable method for suggesting tags for a new text entry. The paper consists of two parts: (i) exploration of existing sample data, which includes statistical analysis and visualisation of the data to provide an overview, and (ii) evaluation of tag prediction approaches. We have included different approaches from different research fields in order to cover a broad spectrum of possible solutions. As a result, we have tested a machine learning model for multi-label classification (using gradient boosting), a statistical approach (using frequency heuristics), and two simple similarity-based classification approaches (Nearest Centroid and k-Nearest Neighbours). The experiment which compares the approaches uses recall to measure the quality of results. Finally, we provide a recommendation of the modelling approach which produces the best accuracy in terms of tag prediction on the sample data

EEG in fitness to drive evaluations in people with epilepsy - Considerable variations across Europe

PURPOSE: Epilepsy patients consider driving issues to be one of their most serious concerns. Ideally, decisions regarding fitness to drive should be based upon thorough evaluations by specialists in epilepsy care. In 2009, an EU directive was published aiming to harmonize evaluation practices within European countries, but, despite these recommendations, whether all epileptologists use the same criteria is unclear. We therefore conducted this study to investigate routine practices on how epileptologists at European epilepsy centers evaluate fitness to drive. METHODS: A questionnaire was sent to 63 contact persons identified through the European Epi-Care and the E-pilepsy network. The questionnaire addressed how fitness-to-drive evaluations were conducted, the involvement of different professionals, the use and interpretation of EEG, and opinions on existing regulations and guidelines. RESULTS: The questionnaire was completed by 35 participants (56 % response rate). Results showed considerable variation regarding test routines and the emphasis placed on the occurrence and extent of epileptiform discharges revealed by EEG. 82 % of the responders agreed that there was a need for more research on how to better evaluate fitness-to-drive in people with epilepsy, and 89 % agreed that regulations on fitness to drive evaluations should be internationally coordinated. CONCLUSION: Our survey showed considerable variations among European epileptologists regarding use of EEG and how findings of EEG pathology should be assessed in fitness-to-drive evaluations. There is a clear need for more research on this issue and international guidelines on how such evaluations should be carried out would be of value