What we talk about when we talk about context

By Paul Dourish. 2004

1,736 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Human-Computer Interaction

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Citations in the corpus

Critique and Contribute: A Practice-Based Framework for Improving Critical Data Studies and Data Science (2017, background): “27 Data scientists in our ﬁeld site made data reuse and sharing possible through their conversations and interactions that brought relevant context to the data.”
Context-Aware Recommender Systems for Learning: A Survey and Future Challenges (2012, background): “Dourish [32] suggests that context has a dual origin: 1) technical and 2) social science based.”
Algorithmic realism: expanding the boundaries of algorithmic thought (2020, background): “Gleaning context therefore requires a porous approach rather than an internalist focus on data [16, 36, 45, 132].”
Understanding experience in interactive systems (2004, background): “Other researchers have examined how mutual understanding and context for action shaped the flow and construction of experience, particularly when interacting with technology [19].”
Discourses on ICT and Development (2010, background): “Two orientations toward addressing issues of context are discernible in the universalistic and situ- ated research streams of IS and HCI research and similarly inºuenced ICTD research (Avgerou & Madon, 2004; Dourish, 2004).”
Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols (2013, background): “, Cn ∈ C (Dourish 2004), where each dimension Ci may have its own type and range of values.”
Trends and Trajectories for Explainable, Accountable and Intelligible Systems: An HCI Research Agenda (2018, background): “Echoing earlier arguments from Suchman [163], researchers critiqued simplistic representations of context [53, 56].”
Context-aware recommender systems (2008, positive): “1 Furthermore, we follow the representational view of Dourish [34], as described at the end of Section 7.”
Toward situated interventions for algorithmic equity: lessons from the field (2020, background): “As Paul Dourish [16] notes, HCI joins distinct scholarly traditions that are often viewed as at oddswith each other: a positivist engineering approach,”
Semantic Multimedia Information Retrieval Based on Contextual Descriptions (2013, background): “computing context is broadly used for two purposes: as retrieval cue and to tailor the behavior and the response type of the system [6].”
Recommender Systems (2016, neutral): “A discussion of how appropriate attributes may be selected for contextual methods is provided in [188].”
Sequence-Aware Recommender Systems (2018, background): “Context factors like these are examples of what is called the representational context [28], which is defined by a predefined set of “observable” context variables.”
The nice thing about context is that everyone has it (2015, background): “‘Essentially’, Dourish (2004) writes, ‘the sociological critique is that the kind of thing that can be modeled […] is not the kind of thing that context is’ (p. 22).”
What Do We Want From Explainable Artificial Intelligence (XAI)? - A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research (2021, background): “, whether there are other people present in a given situation; [163]).”