CAREER: Observing the world through the lenses of social media

每天，世界各地都有数百万人拍照并上传到社交媒体网站。他们的目标是与朋友和其他人分享照片，但他们共同创造了关于世界的巨大视觉信息库。每张照片都是对世界在特定时间和空间点上的观察。这些照片加在一起，可以为生物学、地球科学、社会科学或历史等学科提供新的观测数据来源。该项目正在研究挖掘这些大量照片和嘈杂元数据以推断物理世界所需的算法和技术。该项目有四个研究重点：(1)研究识别和纠正元数据（如地理标签和时间戳）中的噪声的技术；(2)开发从图像和元数据中提取语义信息的算法；(3)创建从多张照片中提取噪声证据的鲁棒聚合方法；(4)在生物学、社会学和地球科学的跨学科应用中验证这些技术。该项目为使用视觉社交媒体作为各种科学学科观测数据的新来源奠定了基础。教育部分是通过新的本科和研究生课程以及在线教学材料，让学生为下一代“大数据”工作做好准备。招募本科生（特别是来自代表性不足群体的本科生）参与研究项目，并鼓励他们从事科学事业。计划每年举办一次讲习班，向普通观众，特别是老年人，介绍数据挖掘和社会媒体。项目的源代码、数据集、课程材料和其他成果将通过项目网站（http://vision.soic.indiana.edu/career/）向公众发布。

Every day, millions of people across the world take photos and upload them to social media websites. Their goal is to share photos with friends and others, but collectively they are creating vast repositories of visual information about the world. Each photo is an observation of how the world looked at a particular point in time and space. Aggregated together, these photos could provide new sources of observational data for use in disciplines like biology, earth science, social science or history. This project is investigating the algorithms and technologies needed for mining these large collections of photographs and noisy metadata to draw inferences about the physical world. The project has four research thrusts: (1) investigating techniques for identifying and correcting noise in metadata like geo-tags and timestamps, (2) developing algorithms for extracting semantic information from images and metadata, (3) creating methods for robust aggregation of noisy evidence from multiple photos, (4) validating these techniques on interdisciplinary applications in biology, sociology, and earth science.The project is laying the foundation for using visual social media as a new source of observational data for a variety of scientific disciplines. The educational component is preparing students for the next generation of "big data" jobs through new undergraduate and graduate courses and online instructional materials. Undergraduate students (particularly from under-represented groups) are recruited to participate in the research program and encouraged to pursue scientific careers. An annual workshop is planned to educate general audiences, particularly senior citizens, about data mining and social media. Source code, datasets, course materials, and other results of the project will be disseminated to the public via the project web site (http://vision.soic.indiana.edu/career/).