90 research outputs found
Natural language processing for Albanian: a state-of-the-art survey
Due to its wide applicability, natural language processing (NLP) has attracted significant research efforts to the machine learning and deep learning research community. Despite this, research works investigating NLP for the Albanian language are still limited. However, to the best of our knowledge, there is no literature review available, which presents a clear picture of what has been studied, argued, and established in the area. The main objective of this survey is to comprehensively review, analyze and discuss the state-of-the-art in NLP for the Albanian language. Here, we present an extensive study concerning the contribution of several authors that have contributed to the application of NLP to the Albanian language. Also, we present an overview of research carried out in the typical applications of NLP for the Albanian language. Finally, some future challenges and limitations of the area are discussed
Mapping (Dis-)Information Flow about the MH17 Plane Crash
Digital media enables not only fast sharing of information, but also
disinformation. One prominent case of an event leading to circulation of
disinformation on social media is the MH17 plane crash. Studies analysing the
spread of information about this event on Twitter have focused on small,
manually annotated datasets, or used proxys for data annotation. In this work,
we examine to what extent text classifiers can be used to label data for
subsequent content analysis, in particular we focus on predicting pro-Russian
and pro-Ukrainian Twitter content related to the MH17 plane crash. Even though
we find that a neural classifier improves over a hashtag based baseline,
labeling pro-Russian and pro-Ukrainian content with high precision remains a
challenging problem. We provide an error analysis underlining the difficulty of
the task and identify factors that might help improve classification in future
work. Finally, we show how the classifier can facilitate the annotation task
for human annotators
What Measures Can Government Institutions in Germany Take Against Digital Disinformation? A Systematic Literature Review and Ethical-Legal Discussion
Disinformation campaigns spread rapidly through social media and can cause serious harm, especially in crisis situations, ranging from confusion about how to act to a loss of trust in government institutions. Therefore, the prevention of digital disinformation campaigns represents an important research topic. However, previous research in the field of information systems focused on the technical possibilities to detect and combat disinformation, while ethical and legal perspectives have been neglected so far. In this article, we synthesize previous information systems literature on disinformation prevention measures and discuss these measures from an ethical and legal perspective. We conclude by proposing questions for future research on the prevention of disinformation campaigns from an IS, ethical, and legal perspective. In doing so, we contribute to a balanced discussion on the prevention of digital disinformation campaigns that equally considers technical, ethical, and legal issues, and encourage increased interdisciplinary collaboration in future research
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