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Publications (12)
Zusammenfassung
Der Umgang mit Hatespeech ist bereits seit mehreren Jahren ein Problem im Internet, insbesondere in sozialen Netzwerken. Da die enorme Menge an Kommentaren nicht mehr manuell moderiert werden kann, ist es essenziell, automatische Methoden zur Detektion offensiver Kommentare unterstützend einzusetzen. Doch speziell in Bezug auf die d...
The automatic detection of disinformation has gained an increased focus by the research community during the last years. The spread of false information can be an issue for political processes, opinion mining and journalism in general. In this dissertation, I propose a novel approach to gain new insights on the automatic detection of disinformation...
Hass und aggressives Verhalten im Netz werden immer größere Probleme. Der bisher etablierte Versuch zur Lösung des Problems ist das Löschen von Kommentaren, doch um dem grundlegenden Problem entgegenzuwirken, müssen Ursachen für die Entstehung von Hass im Netz bekämpft werden. In diesem Kapitel wird daher neben Grundlagen der Hatespeechanalyse insb...
Situational awareness is one of the most important factors for efficient and effective response in crisis and disaster situations. Up-to-date, valid and relevant data is one of the means to support crisis management actions, and the development and use of social media, as it is common nowadays, has become a very interesting research topic. In this...
Digital curation of materials available in large online repositories is required to enable the reuse of Cultural Heritage resources in specific activities like education or scientific research. The digitization of such valuable objects is an important task for making them accessible through digital platforms such as Europeana, therefore ensuring th...
In this work, we present a new publicly available offensive language dataset of 10.278 German social media comments collected in the first half of 2021 that were annotated by in total six annotators. With twelve different annotation categories, it is far more comprehensive than other datasets, and goes beyond just hate speech detection. The labels...
In this paper, we present deep learning frameworks for audio-visual scene classification (SC) and indicate how individual visual, audio features as well as their combination affect SC performance. Our extensive experiments are conducted on DCASE 2021 (IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events) Task 1B Develop...
In this paper, we present deep learning frameworks for audio-visual scene classification (SC) and indicate how individual visual and audio features as well as their combination affect SC performance. Our extensive experiments, which are conducted on DCASE (IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events) Task 1B de...
Sexism has become an increasingly major problem on social networks during the last years. The first shared task on sEXism Identification in Social neTworks (EXIST) at IberLEF 2021 is an international competition in the field of Natural Language Processing (NLP) with the aim to automatically identify sexism in social media content by applying machin...
The automatic detection of disinformation and misinformation has gained attention during the last years, since fake news has a critical impact on democracy, society, and journalism and digital literacy. In this paper, we present a binary content-based classification approach for detecting fake news automatically, with several recently published pre...
