Utilizing Visualization-oriented Natural Language Interfaces (V-NLI) as a complementary
input modality to direct manipulation for visual analytics can provide an engaging user …

Data visualizations can empower an audience to make informed decisions. At the same
time, deceptive representations of data can lead to inaccurate interpretations while still …

Automatic infographics generators employ machine learning algorithms/user-defined rules
and visual embellishments into the creation of infographics. It is an emerging topic in the …

Data visualization is powerful in persuading an audience. However, when it is done poorly
or maliciously, a visualization may become misleading or even deceiving. Visualizations …

Despite the rising popularity of automated visualization tools, existing systems tend to
provide direct results which do not always fit the input data or meet visualization …

Deceptive visualizations are visualizations that, whether intentionally or not, lead the reader
to an understanding of the data which varies from the actual data. Examples of deceptive …

Practitioners from diverse occupations and backgrounds are increasingly using machine
learning (ML) methods. Nonetheless, studies on ML Practitioners typically draw populations …

Translating natural language to visualization (NL2VIS) has shown great promise for visual
data analysis, but it remains a challenging task that requires multiple low-level …

There has been substantial growth in the use of JSON-based grammars, as well as other
standard data serialization languages, to create visualizations. Each of these grammars …

Misleading data visualizations have become a significant issue in our information-rich world
due to their negative impact on informed decision-making. Consequently, it is crucial to …