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Grounding Interactive Machine Learning Tool Design in How Non-Experts Actually Build Models
TLDR
This work investigated how non-experts build ML solutions for themselves in real life and suggested that, while challenging, making ML easy and robust should both be important goals of designing novice-facing ML tools.
Using Machine Learning to Support Qualitative Coding in Social Science
TLDR
The experience of designing a visual analytics tool for collaborative qualitative coding is utilized to demonstrate the potential in using ML to support qualitative coding by shifting the focus to identifying ambiguity and propose three research directions to ground ML applications for social science as part of the progression toward human-centered machine learning.
AnchorViz: Facilitating Classifier Error Discovery through Interactive Semantic Data Exploration
TLDR
The results from the user study show that AnchorViz helps users discover more prediction errors than stratified random and uncertainty sampling methods and examine the inconsistencies between data points that are semantically related.
Lariat: A Visual Analytics Tool for Social Media Researchers to Explore Twitter Datasets
TLDR
The design of Lariat was informed by the results of the formative study and sensemaking theory, both indicating that the exploratory processes require search, comparison, verification, and iterative refinement.
Emoticons in text may function like gestures in spoken or signed communication
TLDR
It is proposed that gesture is likely characterized by a nuanced interdependence with language whether signed, spoken or texted, and that emoticon-based gesture resembles that of gesture in speech.
Emoticons in informal text communication: a new window on bilingual alignment*
The study of emoticon use in text communication is in its early stages (Aragon, Feldman, Chen & Kroll, 2014), with even less known about how emoticons function in multilingual environments. We
Aeonium: Visual analytics to support collaborative qualitative coding
TLDR
The goal was not to reduce qualitative coding to a machine-solvable problem, but rather to bolster human understanding gained from coding and reinterpreting the data collaboratively through the visual analytics interface, Aeonium.
Toward the operationalization of visual metaphor
TLDR
A theoretical conception of metaphor from cognitive linguistics is used to design an interactive system for viewing the citation network of the corpora of literature in the JSTOR database, a highly connected compound graph of 2 million papers linked by 8 million citations.
Considering Time in Designing Large-Scale Systems for Scientific Computing
TLDR
This work utilizes time as a lens to conduct an ethnographic study of scientists interacting with HPC systems and builds upon recent CSCW work to consider temporal rhythms and collective time within the HPC sociotechnical ecosystem and provide considerations for future system design.
AnchorViz: Facilitating Semantic Data Exploration and Concept Discovery for Interactive Machine Learning
TLDR
AnchorViz is an interactive visualization that facilitates the discovery of prediction errors and previously unseen concepts through human-driven semantic data exploration and helps users discover more prediction errors than stratified random and uncertainty sampling methods.
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