Internet traffic is increasingly dominated by user-generated content, predominantly by multimedia content (photos and videos). The content is primarily shared in online social networks (OSNs) such as Pinterest, Twitter, and Facebook. In this thesis, we are interested in studying the traffic imposed by user-generated multimedia content in OSNs and exploring the potential of involving end-user devices for more efficient delivery of user-generated media content. To do so, we developed Viewcount, a Facebook application, to collect traces of user-generated multimedia traffic. Through analyzing social activities around user-generated multimedia content (such as user demographics and viewing distributions), we drew insightful observations correlating demographics and social activities to network traffic. These observations shed light on the design of DEPA, a demographic-driven peer-assisted content delivery network (CDN) to reduce redundant network traffic and workload on the OSN servers. In contrast to existing attempts towards peer-assisted OSNs, DEPA adapts existing OSN architecture and introduces various demographic-driven caching schemes. Through a trace-driven simulator, we evaluated DEPA in both the Viewcount network and on OSNs with different demographic properties. DEPA provided a significant reduction of traffic on the OSN servers even with very small caches on our peer-assistants. Furthermore, the demographic caching algorithm in DEPA is more adaptive to dynamic changes of user online status in OSNs.