Xu talk 3-17-2015

从社会网络和传播内容看社会化媒体资本 Social Media Capital—A Network and

Content Perspective

许未艾，博士候选人美国纽约州立大学布法罗校区

Weiai Xu, PhD CandidateDepartment of Communication, SUNY-Buffalo

curiositybits.com

讲座提纲 Preview

1. My published works on social media 前期关于社会化媒体的研究成果2. My dissertation on social media capital

博士论文：社会化媒体上的社会资本3. Connecting my research insight with big data 对大数据研究的启示与借鉴

观察社会网络的两个视角 Two Tales of Social Networks

社会化媒体上的社会网络，意见领袖和社会资本Social media, social network, social capital and opinion leadership 社会化媒体传播的两个关键因素：社会关系（ connections ）和传播内容（ content ）

研究方向 My research program

政治动员Political activism

文化传播Cultural diffusion

媒体人受众互动Audience interaction

医疗信息传播Health communication

个体用户政治表达与参与Political self-presentation

Xu, W.W., Sang, Y.M., Blasiola, S., & Park, H.W. (2014). Predicting opinion leaders in Twitter activism networks: The case of the Wisconsin recall election. American Behavioral Scientist, 58(10), 1278-93.

community

information

Network— 位居社会网络的核心 Content— 互动性内容的发布者

社会化媒体上的意见领袖 Networked Opinion LeadershipTwo key factors in strategic public communication: central/bridging network position and engaging content that is conversational and with clear call-to-action cues

Xu, W. W., Park, J. Y., & Park, H. W. (2015). The networked cultural diffusion of Korean Wave. Online Information Review, 39(1).

社会化媒体上的文化传播 Networked Cultural Diffusion

YouTube 用户关注和评论关系图

Xu, W.W., Park, J.Y., & Park, H.W. (2014). Networked cultural diffusion and creation on YouTube: A network analysis of YouTube memes. Resubmission under review by Journal of Broadcasting & Electronic Media.


YouTube 用户原创视频主题关系图


YouTube 用户评论的语义分析（ Semantic network analysis ）



用户特征用户原创内容

用户关系特征


Xu, W.W., Chiu, I., Chen, Y., & Mukherjee, T. (2014). Twitter Hashtags for Health - Applying Network and Content Analyses to Understand the Health Knowledge Sharing in a Twitter-based Community of Practice. Quality & Quantity, 1-20.

社会化媒体上的健康传播 Networked Health Communication

Twitter 用户评论关系图

Xu, W.W., Chiu, I., Chen, Y., & Mukherjee, T. (2014). Twitter Hashtags for Health - Applying Network and Content Analyses to Understand the Health Knowledge Sharing in a Twitter-based Community of Practice. Quality & Quantity, 1-20.

社会化媒体上的健康传播 Networked Health Communication

Twitter 用户讨论的内容分析（ content analysis ）

Xu, W.W. & Feng, M. (2014). Talking to the Broadcasters to Broadcast, on Twitter - Twitter Conversations with Journalists as a Practice of Networked Gatekeeping. Journal of Broadcasting & Electronic Media, 58(3), 420-37

社会化媒体上的观众互动 Networked Gatekeeping

Twitter 用户评论关系图

Xu, W.W. & Feng, M. (2014). Talking to the Broadcasters to Broadcast, on Twitter - Twitter Conversations with Journalists as a Practice of Networked Gatekeeping. Journal of Broadcasting & Electronic Media, 58(3), 420-37

社群媒体上的观众互动 Networked Gatekeeping

Twitter 用户谈话的内容分析（ content analysis ）

博士论文：社会化媒体上的社会资本Dissertation: Predicting Social Capital in Stakeholder Communication in Social Media

1. Define social media capital (SMC) 线上社会资本2. Develop a webometric framework to gauge social media capital线上社会资本的量化指标3. Develop a predictive model for social media capital ROI 线上社会资本投入产出的预测模型

背景：非盈利组织同公众和利益相关者的线上互动Background: Nonprofits’ online stakeholder engagement

线上社会资本的构成Elements of Social Media Capital

Social Capital Investment

Social Media Capital

Social Capital Return

社会资本投入社会资本的量化形态社会资本产出• Message-based• Connection-based

• Network locations • Embedded resources

Bourdieu, P. (1989). Social space and symbolic power. Sociological theory,7(1), 14-25.Lin, N. (1999). Building a network theory of social capital. Connections, 22(1), 28-51.

• Word-of-mouth

线上社会资本的量化指标Webometrics for Social Media Capital

Social Capital Investment社会资本投入的量化

SMC 社会资本的量化

Social Capital Return社会资本产出

Message-based1. The # of tweets2. Message complexity

Connection-based3. The # of targeted local

stakeholders4. The # of targeted non-local

stakeholders5. Frequency of stakeholder-

targeting6. Variety of targeted

stakeholders

Network locations1. Betweenness centrality in inter-

organization follower network2. In-degree centrality in inter-

organization follower network

Embedded resources3. The size of acquired stakeholder

network4. The influence of acquired

stakeholders5. The strength of ties with acquired

stakeholders6. The variety of acquired stakeholders

The # of retweets per tweet

社会资本投入社会资本的形态社会资本产出

线上社会资本预测模型Social Media Capital Model

数据来源和研究方法Data Collection and Methods

• Data downloaded through Twitter API using Python

• 258 U.S-based community foundations' Twitter activities.

• All tweets sent by and to the community foundations, with a special emphasis on directed tweet

• 通过 Python 语言进行 Twitter上的数据挖掘

• 研究对象为 258 个美国的社区基金会

• 社会网络分析，内容分析

社会资本投入和社会资本总量的关系How SMC Investment Predicts the Acquisition of SMC

SMC Investment社会资本投入的量化


Embedded resources1. The size of acquired

stakeholder network2. The influence of acquired

stakeholders3. The strength of ties with

acquired stakeholders4. The variety of acquired

stakeholders

+.24**

+.13**

+.21**


Connection-based3. The # of local targeted

stakeholders4. The # of non-local targeted



stakeholders

F (8, 193) = 36.44, .59**








stakeholders+.24**






stakeholders

F (8, 193) = 8.41, .23**

+.18**








stakeholders+.36**






stakeholders

F (8, 193) = 8.29, .23**








stakeholders+.34**






stakeholders

F (8, 193) = 26.24, .50**

+.11**

线上社会资本投入和社会资本总量的关系How SMC Investment Predicts the Acquisition of SMC








stakeholders

Network locations1. Betweenness centrality in

inter-organization follower network

2. In-degree centrality in inter-organization follower network

-.25**

+.15**

+.38**

F (8, 193) = 13.74, .34**

线上社会资本投入和社会资本总量的关系How SMC Investment Predicts the Acquisition of SMC








stakeholders

Network locations1. Betweenness centrality in

inter-organization follower network

2. In-degree centrality in inter-organization follower network

-.31**

+.18**

+.43**

F (8, 193) = 8.84, .27**

社会资本和社会资本产出的关系How SMC Predicts SMC Return


Network locations1. In-degree centrality in inter-

organization follower networkEmbedded resources2. The size of acquired local

stakeholder network3. The size of acquired non-local



stakeholders6. The variety of acquired

stakeholders

+.15*

SMC Return社会资本产出

The # of retweets

+.41*

F (7, 194) = 17.30, .36**

社会资本和社会资本产出的关系How SMC Predicts SMC Return


Network locations1. Betweenness centrality in inter-

organization follower networkEmbedded resources2. The size of acquired local

stakeholder network3. The size of acquired non-local



stakeholders6. The variety of acquired

stakeholders

SMC Return社会资本产出

The # of retweets

+.43*

F (7, 194) = 16.78, .36**

总结Takeaway

• To garner word-of-mouth in online stakeholder engagement, organizations must acquire social media capital, specifically, they need to build a large network of diverse, local and influential stakeholders.

• To acquire social media capital, organizations must invest in creating multi-format messages and direct the messages at a large number of diverse and local stakeholders.

对大数据研究的意义Implications for Big-data Research

对大数据研究的意义Implications for Big-data Research

• Integrating network and content analyses in understanding online public opinion 结合网络分析和内容分析调查网络舆情

• Webometrics for government-public relationship on social media 使用网络测量学研究线上政府公众关系

Technology

Xu talk 3-17-2015