Incremental visual text analytics of news story development

Krstajic, Milos; Najm-Araghi, Mohammad; Mansmann, Florian; Keim, Daniel A.

doi:10.1117/12.912456

Cited by 9 publications

(8 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…News analysis has been a main target for visual analytics applications, for which the literature is prolific. The majority of related work explores text-based news data ( [6], [7], [8], [9], [10], [11], [12], [13], [14], [15]), the focus of which was often on event and topic analysis, to reveal stories to users. Although we wanted to differentiate our study from these by solely focusing on the cues we extract from the visual information of the videos, we also incorporated political affiliations in our design.…”

Section: Related Workmentioning

confidence: 99%

“…While some studies were aimed at supporting the understanding of news stories by delivering a summary of their content ( [16], [13], [8], [6]) others were aimed at delivering the actual content depending on users' analysis ( [17], [9], [10], [18]). Incidentally, the latter case appears mostly with systems involving video information, whether users are experts or not, for whom watching the content is often a necessary task.…”

Section: Related Workmentioning

confidence: 99%

“…Many visual analytics systems are focused on the coordination of timelines ( [18], [10], [6], [8], [7], [9]). They often include the representation of the topics themselves, e.g.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Visual Analytics of Political Networks From Face-Tracking of News Video

Renoust

Satoh

2016

IEEE Trans. Multimedia

View full text Add to dashboard Cite

The rich nature of news makes it a classic subject of visual analytics research. Such analysis is often based on rich textual data. However, we want to test how much we can understand the news from video information through face detection and tracking. Towards this goal, we propose a visual analytics system and discuss its design and implementation to support media experts in understanding political interactions in an archive of twelve years of the Japanese public broadcaster NHK's News 7 program. After identifying the tasks and abstraction required for our analysis, we construct links from face detection and tracking to derive multiple political networks. Our proposed design embeds this rich data into a visual analytics framework that presents four levels of abstraction: time period, network, timeline, and face-tracks within video. We present how the exploration of the archive with our system results in good understanding of the Japanese politico-media scene during these twelve years while finding evidence of "presidentialization" of the media.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Visual Analytics of Political Networks From Face-Tracking of News Video

Renoust

Satoh

2016

IEEE Trans. Multimedia

View full text Add to dashboard Cite

show abstract

“…Features can reoccur at another point in time, which leads to connections between features. A similar approach has been presented by Krstajic et al [23]. The authors use an approach similar to Themeriver [24], but discretize time (x-axis) and visualize news articles developments, instead of features, over time.…”

Section: Visualization Approachesmentioning

confidence: 99%

Visual Soccer Analytics: Understanding the Characteristics of Collective Team Movement Based on Feature-Driven Analysis and Abstraction

Stein

Häußler

Jäckle

et al. 2015

IJGI

View full text Add to dashboard Cite

With recent advances in sensor technologies, large amounts of movement data have become available in many application areas. A novel, promising application is the data-driven analysis of team sport. Specifically, soccer matches comprise rich, multivariate movement data at high temporal and geospatial resolution. Capturing and analyzing complex movement patterns and interdependencies between the players with respect to various characteristics is challenging. So far, soccer experts manually post-analyze game situations and depict certain patterns with respect to their experience. We propose a visual analysis system for interactive identification of soccer patterns and situations being of interest to the analyst. Our approach builds on a preliminary system, which is enhanced by semantic features defined together with a soccer domain expert. The system includes a range of useful visualizations to show the ranking of features over time and plots the change of game play situations, both helping the analyst to interpret complex game situations. A novel workflow includes improving the analysis process by a learning stage, taking into account user feedback. We evaluate our approach by analyzing real-world soccer matches, illustrate ISPRS Int. J. Geo-Inf. 2015, 4 2160 several use cases and collect additional expert feedback. The resulting findings are discussed with subject matter experts.

show abstract

“…Fig. 4, for example, shows a Visual Analytics system for the analysis of online news [14] collected by the Europe Media Monitor 7 . Text clustering is used to extract stories from the news articles and to detect merging and splitting events in such stories.…”

Section: Text and News Analysismentioning

confidence: 99%

Visual Analytics: Towards Intelligent Interactive Internet and Security Solutions

Davey

Mansmann

Kohlhammer

et al. 2012

The Future Internet

Self Cite

View full text Add to dashboard Cite

Abstract. In the Future Internet, Big Data can not only be found in the amount of traffic, logs or alerts of the network infrastructure, but also on the content side. While the term big data refers to the increase of the available data, this implicitly means that we must deal with problems at larger scale and thus hints at scalability issues in the analysis process of such data sets. Visual Analytics is an enabling technology, that offers new ways of extracting information from big data through intelligent, interactive internet and security solutions. It derives its effectiveness both from scalable analysis algorithms, that allow processing of large data sets, and from scalable visualizations. These visualizations take advantage of human background knowledge and pattern detection capabilities to find yet unknown patterns, to detect trends and to relate these findings to a holistic view on the problems. Besides discussing the origins of Visual Analytics, this paper presents concrete examples of how the two facets of content and infrastructure of the Future Internet can benefit from Visual Analytics. In conclusion, it is the confluence of both technologies that will open up new opportunities for businesses, e-governance and the public.

show abstract

Incremental visual text analytics of news story development

Cited by 9 publications

References 19 publications

Visual Analytics of Political Networks From Face-Tracking of News Video

Visual Analytics of Political Networks From Face-Tracking of News Video

Visual Soccer Analytics: Understanding the Characteristics of Collective Team Movement Based on Feature-Driven Analysis and Abstraction

Visual Analytics: Towards Intelligent Interactive Internet and Security Solutions

Contact Info

Product

Resources

About