Online misogyny, a category of online abusive language, has serious and harmful social consequences. Automatic detection of misogynistic language online, while imperative, poses complicated challenges to both data gathering, data annotation, and bias mitigation, as this type of data is linguistically complex and diverse. This paper makes three contributions in this area: Firstly, we describe the detailed design of our iterative annotation process and codebook. Secondly, we present a comprehensive taxonomy of labels for annotating misogyny in natural written language, and finally, we introduce a high-quality dataset of annotated posts sampled from social media posts.

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This article presents a grounded theory analysis based on a qualitative study of professional interaction designers ( n = 20) with a focus on how they use tools to manage design ideas. Idea management can be understood as a subcategory of the field personal information management, which includes the activities around the capture, organization, retrieval, and use of information. Idea management pertains to the management and use of ideas , a particular type of information, as part of creative activities. The article identifies tool-supported idea management strategies and needs of professional interaction designers, and discusses the context and consequences of these strategies. Based on our analysis, we identify a conceptual framework of 10 strategies which are supported by tools: saving, externalizing, advancing, exploring, archiving, clustering, extracting, browsing, verifying, and collaborating . Finally, we discuss how this framework can be used to characterize and analyze existing and novel idea management tools.

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Misinformation spread presents a technological and social threat to society. With the advance of AI-based language models, automatically generated texts have become difficult to identify and easy to create at scale. We present "The Rumour Mill", a playful art piece, designed as a commentary on the spread of rumours and automatically-generated misinformation. The mill is a tabletop interactive machine, which invites a user to experience the process of creating believable text by interacting with different tangible controls on the mill. The user manipulates visible parameters to adjust the genre and type of an automatically generated text rumour. The Rumour Mill is a physical demonstration of the state of current technology and its ability to generate and manipulate natural language text, and of the act of starting and spreading rumours.

Elections are a time when communication is important in democracies, including over social media. This paper describes a case study of applying NLP to determine the extent to which misinformation and external manipulation were present on Twitter during a national election. We use three methods to detect the spread of misinformation: analysing unusual spatial and temporal behaviours; detecting known false claims and using these to estimate the total prevalence; and detecting amplifiers through language use. We find that while present, detectable spread of misinformation on Twitter was remarkably low during the election period in Denmark.

Research ideas are pivotal in research practice. While research domains, topics, and methods are often outlined by specific research fields, the process of capturing and developing research ideas is less categorical. Conceiving and developing research ideas requires continuous creative thinking, usually supported by various different tools, each more or less carefully selected by a researcher to fulfill a specific purpose. In this paper, we investigate the creative work practices of academic researchers, with a focus on the workflows and tools they employ to manage ideas. Through a qualitative survey (𝑛=51) and in-depth interviews (𝑛=18) with researchers from a wide range of fields, we identify and describe typical processes of managing research ideas, different types of research ideas (a research question or problem, a method, a hypothesis or antithesis, and a theory), properties of good research ideas, as well as potentials for tools and technology to support idea management for researchers.CCS Concepts: • Social and professional topics → User characteristics; • Human-centered computing → User studies.