Nicholas Diakopoulos

Characterizing debate performance via aggregated twitter sentiment

Television broadcasters are beginning to combine social micro-blogging systems such as Twitter with television to create social video experiences around events. We looked at one such event, the first U.S. presidential debate in 2008, in conjunction with aggregated ratings of message sentiment from Twitter. We begin to develop an analytical methodology and visual representations that could help a journalist or public affairs person better understand the temporal dynamics of sentiment in reaction to the debate video. We demonstrate visuals and metrics that can be used to detect sentiment pulse, anomalies in that pulse, and indications of controversial topics that can be used to inform the design of visual analytic systems for social media events.

Diamonds in the rough: Social media visual analytics for journalistic inquiry

Journalists increasingly turn to social media sources such as Facebook or Twitter to support their coverage of various news events. For large-scale events such as televised debates and speeches, the amount of content on social media can easily become overwhelming, yet still contain information that may aid and augment reporting via individual content items as well as via aggregate information from the crowds response. In this work we present a visual analytic tool, Vox Civitas, designed to help journalists and media professionals extract news value from large-scale aggregations of social media content around broadcast events. We discuss the design of the tool, present the text analysis techniques used to enable the presentation, and provide details on the visual and interaction design. We provide an exploratory evaluation based on a user study in which journalists interacted with the system to explore and report on a dataset of over one hundred thousand twitter messages collected during the U.S. State of the Union presidential address in 2010.

Unfolding the event landscape on twitter: classification and exploration of user categories

Social media platforms such as Twitter garner significant attention from very large audiences in response to real-world events. Automatically establishing who is participating in information production or conversation around events can improve event content consumption, help expose the stakeholders in the event and their varied interests, and even help steer subsequent coverage of an event by journalists. In this paper, we take initial steps towards building an automatic classifier for user types on Twitter, focusing on three core user categories that are reflective of the information production and consumption processes around events: organizations, journalists/media bloggers, and ordinary individuals. Exploration of the user categories on a range of events shows distinctive characteristics in terms of the proportion of each user type, as well as differences in the nature of content each shared around the events.

Videotater: an approach for pen-based digital video segmentation and tagging

The continuous growth of media databases necessitates development of novel visualization and interaction techniques to support management of these collections. We present Videotater, an experimental tool for a Tablet PC that supports the efficient and intuitive navigation, selection, segmentation, and tagging of video. Our veridical representation immediately signals to the user where appropriate segment boundaries should be placed and allows for rapid review and refinement of manually or automatically generated segments. Finally, we explore a distribution of modalities in the interface by using multiple timeline representations, pressure sensing, and a tag painting/erasing metaphor with the pen.

Mediating photo collage authoring

The medium of collage supports the visualization of meaningful event summaries using photographs. It can however be rather tedious to author a collage from a large collection of photographs. In this work we present an approach that supports efficient construction of a collage by assisting the user with an automatic layout procedure that can be controlled at a high level. Our layout method utilizes a pre-designed template which consists of cells for photos and annotations applied to these cells. The layout is then filled by matching the metadata of photos to the annotations in the cells using an optimization algorithm. The user exercises flexibility in the authoring process by (a) maintaining high-level control through the types of constraints applied and (b) leveraging visual emphases supported by the layout algorithm. The user can of course provide fine-grained control of the final collage through direct manipulation. Off-loading the tedium of collage construction to a user controlled yet automated process clears the way for rapidly generating different views of the same album and could also support the increased sharing of digital photos in the form of compact collages.

Playable data: characterizing the design space of game-y infographics

This work explores the intersection between infographics and games by examining how to embed meaningful visual analytic interactions into game mechanics that in turn impact user behavior around a data-driven graphic. In contrast to other methods of narrative visualization, games provide an alternate method for structuring a story, not bound by a linear arrangement but still providing structure via rules, goals, and mechanics of play. We designed two different versions of a game-y infographic, Salubrious Nation, and compared them to a non-game-y version in an online experiment. We assessed the relative merits of the game-y approach of presentation in terms of exploration of the visualization, insights and learning, and enjoyment of the experience. Based on our results, we discuss some of the benefits and drawbacks of our designs. More generally, we identify challenges and opportunities for further exploration of this new design space.

Content Based Image Synthesis

A new method allowing for semantically guided image editing and synthesis is introduced. The editing process is made considerably easier and more powerful with our content-aware tool. We construct a database of image regions annotated with a carefully chosen vocabulary and utilize recent advances in texture synthesis algorithms to generate new and unique image regions from this database of material. These new regions are then seamlessly composited into a user’s existing photograph. The goal is to empower the end user with the ability to edit existing photographs and synthesize new ones on a high semantic level. Plausible results are generated using a small prototype database and showcase some of the editing possibilities that such a system affords.

Videolyzer: quality analysis of online informational video for bloggers and journalists

Tools to aid people in making sense of the information quality of online informational video are essential for media consumers seeking to be well informed. Our application, Videolyzer, addresses the information quality problem in video by allowing politically motivated bloggers or journalists to analyze, collect, and share criticisms of the information quality of online political videos. Our interface innovates by providing a fine-grained and tightly coupled interaction paradigm between the timeline, the time-synced transcript, and annotations. We also incorporate automatic textual and video content analysis to suggest areas of interest for further assessment by a person. We present an evaluation of Videolyzer looking at the user experience, usefulness, and behavior around the novel features of the UI as well as report on the collaborative dynamic of the discourse generated with the tool.

Topicality, time, and sentiment in online news comments

In this paper we examine the relationships between news comment topicality, temporality, sentiment, and quality in a dataset of 54,540 news comments. Initial observations indicate that comment sentiments, both positive and negative, can be useful indicators of discourse quality, and that aggregate temporal patterns in positive sentiment exist on comment threads.

Audio Puzzler: piecing together time-stamped speech transcripts with a puzzle game

We have developed an audio-based casual puzzle game which produces a time-stamped transcription of spoken audio as a by-product of play. Our evaluation of the game indicates that it is both fun and challenging. The transcripts generated using the game are more accurate than those produced using a standard automatic transcription system and the time-stamps of words are within several hundred milliseconds of ground truth.