Social media is useful for collecting data directly related to humans, such as data regarding actions, interests, and emotions. This article introduces three kinds of examples for the visualization of social data. The first example is the visualization of the ranking of interesting topics; the rankings of topics and their daily fluctuations on Twitter are visualized. It shows rising-patterns, continuity, and burst of topics. The second example is the visualization of spatial distribution of emotions; the occurrence of emotions is represented using isobaric lines on maps. It shows the occurrence and the spread of emotions. The third example is the visualization of temporal-patterns of actions; actions tweeted as something "now" are placed on a two-dimensional plane. It shows the averages and dispersion of the occurrence times of actions.
Large scale graph visualization is often required to analyze phenomenon on web media through the hyperlink structure of the web, friend networks on social networks, and paths of information diffusion. Our research group have built large scale archive of web media including 30 billion Japanese web pages, and posts on blogs and microblogs. In this paper, we first introduce our interactive visualization system for large hierarchical graphs. Then, we show several examples of web media analysis using that system.
In this paper, in order to reveal the characteristics and functions of many networks with complex structure, we explain a framework that extracts communities with different point of view and colors all the nodes of visualization results according to the extracted communities. In real networks, each node has intrinsic functions and roles, and mutually affects on other nodes. In this paper, different from existing community of densely connected nodes, we extract the nodes with similar functions, referred to as functional community. Concretely, we calculate the PageRank score convergence curve of each node and divide all nodes by similarities of these curves as functional community. Finally we color all the node with respect to functional community. From experimental results using artificial and real networks, we confirm that our framework can extract adequate functional communities.
In current society, we can easily and rapidly publish information on our personal activities and interests using social media including blogs and microblogs. They are considered to provide valuable information from the viewpoints of sociology, linguistics, marketing, and urban planning. This paper introduces five 3D information visualization systems developed by authors for analyzing temporal changes in social media contents: 3D visualization systems for 1) tracing influencers in a blog space using time-series of web graphs, 2) analyzing temporal changes in bloggers’ activities and interests through interacting with phrase dependency structures in sentences, 3) analyzing visual trends based on clustering images in blog articles, 4) inter-media comparison through images extracted from different types of media, and 5) spatio-temporal events extracted from a geo-parsed twitter stream. We also introduce several case studies to demonstrate the usefulness of our introducing systems.
Due to the progress and development of the Internet, cyberattacks continue increasing in both quantity and quality from day to day, and it becomes a serious social problem. NICT (National Institute of Information and Communications Technology) have developed the Network Incident analysis Center for Tactical Emergency Response (NICTER), which is an integrated system for monitoring and analysis of cyberattacks. In this manuscript, we report an overview of the visualization technologies in the field of cybersecurity with a focus on NICTER and its spin-off technologies.
April 03, 2017 There had been a system trouble from April 1, 2017, 13:24 to April 2, 2017, 16:07(JST) (April 1, 2017, 04:24 to April 2, 2017, 07:07(UTC)) .The service has been back to normal.We apologize for any inconvenience this may cause you.
May 18, 2016 We have released “J-STAGE BETA site”.
May 01, 2015 Please note the "spoofing mail" that pretends to be J-STAGE.