n Tzy Li

Social media use by government: From the routine to the critical

Abstract Social media and online services with user-generated content (e.g., Twitter, Facebook, Flickr, YouTube) have made a staggering amount of information (and misinformation) available. Government officials seek to leverage these resources to improve services and communication with citizens. Significant potential exists to identify issues in real time, so emergency managers can monitor and respond to issues concerning public safety. Yet, the sheer volume of social data streams generates substantial noise that must be filtered in order to detect meaningful patterns and trends. Important events can then be identified as spikes in activity, while event meaning and consequences can be deciphered by tracking changes in content and public sentiment. This paper presents findings from a exploratory study we conducted between June and December 2010 with government officials in Arlington, VA (and the greater National Capitol Region around Washington, D.C.), with the broad goal of understanding social media use by government officials as well as community organizations, businesses, and the public at large. A key objective was also to understand social media use specifically for managing crisis situations from the routine (e.g., traffic, weather crises) to the critical (e.g., earthquakes, floods).

Social media use by government: from the routine to the critical

Social media (i.e., Twitter, Facebook, Flickr, YouTube) and other services with user-generated content have made a staggering amount of information (and misinformation) available. Government officials seek to leverage these resources to improve services and communication with citizens. Yet, the sheer volume of social data streams generates substantial noise that must be filtered. Nonetheless, potential exists to identify issues in real time, such that emergency management can monitor and respond to issues concerning public safety. By detecting meaningful patterns and trends in the stream of messages and information flow, events can be identified as spikes in activity, while meaning can be deciphered through changes in content. This paper presents findings from a pilot study we conducted between June and December 2010 with government officials in Arlington, Virginia (and the greater National Capitol Region around Washington, DC) with a view to understanding the use of social media by government officials as well as community organizations, businesses and the public. We are especially interested in understanding social media use in crisis situations (whether severe or fairly common, such as traffic or weather crises).

A visual approach for video geocoding using bag-of-scenes

This paper presents a novel approach for video representation, called bag-of-scenes. The proposed method is based on dictionaries of scenes, which provide a high-level representation for videos. Scenes are elements with much more semantic information than local features, specially for geotagging videos using visual content. Thus, each component of the representation model has self-contained semantics and, hence, it can be directly related to a specific place of interest. Experiments were conducted in the context of the MediaEval 2011 Placing Task. The reported results show our strategy compared to those from other participants that used only visual content to accomplish this task. Despite our very simple way to generate the visual dictionary, which has taken photos at random, the results show that our approach presents high accuracy relative to the state-of-the art solutions.

A rank aggregation framework for video multimodal geocoding

This paper proposes a rank aggregation framework for video multimodal geocoding. Textual and visual descriptions associated with videos are used to define ranked lists. These ranked lists are later combined, and the resulting ranked list is used to define appropriate locations for videos. An architecture that implements the proposed framework is designed. In this architecture, there are specific modules for each modality (e.g, textual and visual) that can be developed and evolved independently. Another component is a data fusion module responsible for combining seamlessly the ranked lists defined for each modality. We have validated the proposed framework in the context of the MediaEval 2012 Placing Task, whose objective is to automatically assign geographical coordinates to videos. Obtained results show how our multimodal approach improves the geocoding results when compared to methods that rely on a single modality (either textual or visual descriptors). We also show that the proposed multimodal approach yields comparable results to the best submissions to the Placing Task in 2012 using no extra information besides the available development/training data. Another contribution of this work is related to the proposal of a new effectiveness evaluation measure. The proposed measure is based on distance scores that summarize how effective a designed/tested approach is, considering its overall result for a test dataset.

Twitter use during an emergency event: the case of the UT Austin shooting

This poster presents one of our efforts in the context of the Crisis, Tragedy, and Recovery Network (CTRnet) project. One topic studied in this project is the use of social media by government to respond to emergency events in towns and counties. Monitoring social media information for unusual behavior can help identify these events once we can characterize their patterns. As an example, we analyzed the campus shooting in the University of Texas, Austin, on September 28, 2010. In order to study the pattern of communication and the information communicated using social media on that day, we collected publicly available data from Twitter. Collected tweets were analyzed and visualized using the Natural Language Toolkit, word clouds, and graphs. They showed how news and posts related to this event swamped the discussions of other issues.

Multimedia multimodal geocoding

This work is developed in the context of the placing task of the MediaEval 2011 initiative. The objective is to geocode (or geotag) a set of videos, i.e., automatically assign geographical coordinates to them. This paper presents an architecture for multimodal geocoding that exploits both visual and textual descriptions associated with videos. This work also describes our efforts regarding the implementation of this architecture to demonstrate its applicability. Conducted experiments show how our multimodal approach enhances the results compared to relying on a single modality.

CTRnet DL for disaster information services

We describe our work in collecting, analyzing and visualizing online information (e.g., Web documents, images, tweets), which are to be maintained by the Crisis, Tragedy and Recovery Network (CTRnet) digital library. We have been collecting resources about disaster events, as well as campus and other major shooting events, in collaboration with the Internet Archive (IA). Social media data (e.g., tweets, Facebook data) also have been collected and analyzed. Analyzed results are visualized using graphs and tag clouds. Exploratory content-based image retrieval has been applied in one of our image collections. We explain our CTR ontology development methodology and collaboration with Arlington County, VA and IBM, in a Center for Community Security and Resilience funded project.

Use of subimages in fish species identification: a qualitative study

Many scholarly tasks involve working with subdocuments, or contextualized fine-grain information, i.e., with information that is part of some larger unit. A digital library (DL) facilitates management, access, retrieval, and use of collections of data and metadata through services. However, most DLs do not provide infrastructure or services to support working with subdocuments. Superimposed information (SI) refers to new information that is created to reference subdocuments in existing information resources. We combine this idea of SI with traditional DL services, to define and develop a DL with SI (SI-DL). We explored the use of subimages and evaluated the use of SuperIDR, a prototype SI-DL, in fish species identification, a scholarly task that involves working with subimages. The contexts and strategies of working with subimages in SuperIDR suggest new and enhanced support (SI-DL services) for scholarly tasks that involve working with subimages, including new ways of querying and searching for subimages and associated information. The main conceptual contributions of our work are the insights gained from these findings of the use of subimages and of SuperIDR, which lead to recommendations for the design of digital libraries with superimposed information.

Domain-specific image geocoding: a case study on Virginia tech building photos

The use of map-based browser services is of great relevance in numerous digital libraries. The implementation of such services, however, demands the use of geocoded data collections. This paper investigates the use of image content local representations in geocoding tasks. Performed experiments demonstrate that some of the evaluated descriptors yield effective results in the task of geocoding VT building photos. This study is the first step to geocode multimedia material related to the VT April 16, 2007 school shooting tragedy.

SuperIDR: A Tool for Fish Identification and Information Retrieval

ABSTRACT Students, fisheries professionals, and the general public may value computer-facilitated assistance for fish identification and access to ecological and life history information. We developed SuperIDR, a software package supporting such applications, by utilizing the search and data retrieval capabilities of digital libraries, as well as key features of tablet PCs. We demonstrated SuperIDR utilizing a database with information on 207 freshwater fishes of Virginia. A user may annotate fish images and identify fishes by using a dichotomous key; searching for key words, similar images, subimages, or annotations on images; or combinations of these approaches. Students using the software demonstrated enhanced ability to correctly identify specimens. Their comments led to improvements, including the addition of new features. The PC-based system for identifying freshwater fishes of Virginia may be downloaded and modified. SuperIDR is a prototype for PC-based species identification applications—the syste...