SensePlace3: a geovisual framework to analyze place–time–attribute information in social media

SensePlace3 (SP3) is a geovisual analytics framework and web application that supports overview + detail analysis of social media, focusing on extracting meaningful information from the Twitterverse. SP3 leverages social media related to crisis events. It differs from most existing systems by enabling an analyst to obtain place-relevant information from tweets that have implicit as well as explicit geography. Specifically, SP3 includes not just the ability to utilize the explicit geography of geolocated tweets but also analyze implicit geography by recognizing and geolocating references in both tweet text, which indicates locations tweeted about, and in Twitter profiles, which indicates locations affiliated with users. Key features of SP3 reported here include flexible search and filtering capabilities to support information foraging; an ingest, processing, and indexing pipeline that produces near real-time access for big streaming data; and a novel strategy for implementing a web-based multi-view visual interface with dynamic linking of entities across views. The SP3 system architecture was designed to support crisis management applications, but its design flexibility makes it easily adaptable to other domains. We also report on a user study that provided input to SP3 interface design and suggests next steps for effective spatiotemporal analytics using social media sources.

SensePlace3（SP3）是一款地理可视分析（geovisual analytics）框架与Web应用，支持对社交媒体开展概览与细节分析，核心目标为从推特全域（Twitterverse）中提取有价值的信息。SP3依托与危机事件相关的社交媒体数据开展工作，与绝大多数现有系统的不同之处在于，其允许分析师从兼具隐式地理信息（implicit geography）与显式地理信息的推文中获取与地点相关的内容。具体而言，SP3不仅可利用已地理定位推文（geolocated tweets）的显式地理信息，还能通过识别并地理定位两类提及内容——推文文本中所指代的讨论地点、推特用户资料中所标注的用户所属关联地点，以此实现对隐式地理信息的分析。本文所介绍的SP3关键特性包括：可支撑信息觅食（information foraging）的灵活搜索与过滤功能；可对大规模流数据（big streaming data）实现近乎实时访问的摄取-处理-索引流水线（ingest, processing, and indexing pipeline）；以及一种新颖的实现策略，可搭建支持跨视图实体动态联动的Web端多视图可视化界面（multi-view visual interface）。SP3的系统架构（system architecture）最初专为支撑危机管理（crisis management）应用而设计，但其设计具备较强灵活性，可轻松适配其他应用领域。此外，本文还报告了一项用户研究（user study），该研究为SP3的界面设计提供了参考依据，并提出了依托社交媒体数据源开展高效时空分析（spatiotemporal analytics）的后续发展方向。