SOCIAL NETWORK ANALYSIS | FEB 2014
IREXtech Explains: Social Network Analysis Understanding practical approaches to technology for development This brief condenses lessons shared in the IREX | Center for Collaborative Technology Deep Dive on Social Network Analysis. Through its Deep Dive series, the Center hosts top thinkers and doers in the ICT4D field for short discussions that hash through the buzz around the use of emerging technologies to focus on their practical and substantive applications to development, with the hope that participants walk away with useful information and an understanding of innovative new tech tools. Why analyze social networks? Offline social networks existed and flourished long before social media. For centuries, people capitalized on social networks to make new connections, to influence opinions, and to spread ideas. And analysis of those networks — the study of social actors and ties between them — predates the Internet. Social network analysis (SNA) is a method of exploring levels of influence and social connections, and it is much larger than social media. It can reveal insights into real world communities, useful for advertising and advocacy. For all analysis projects, it is essential to identify three main actors: hubs, who know and are known to many; bridges, who span different groups; and islands, who are not connected to a target group, though may be connected to other groups.
Not all connections are the same. Strong ties are connections that are regularly maintained and have strong influence. Often, those with strong ties will not introduce new information to the network; they tend to recirculate the same types of ideas and opinions on a consistent set of topics. Weak ties are connections that can be infrequent or have little dayto-day influence. However, weak ties are often more conducive to innovation because they convey information that is new to the social actor or group.
Tools: Analyzing social networks, online and off New tools are changing the SNA landscape, making it easy to quickly analyze networks. During the IREXtech Deep Dive on Social Network Analysis, Marc Smith, Director of the Social Media Research Foundation, led a group of international
Offline social networks existed long before social media, and analysis of those networks predates the Internet.
development practitioners through a detailed tutorial of NodeXL, a powerful online tool that creates visualizations of social networks.
SNA tools: The basics From something as simple as a list of people and their tweets, or as complex as a list of every mention of Alexander the Great in ancient literature, NodeXL can visualize a variety of network patterns. NodeXL is Open Source freeware — anyone can use the tool on a computer running Microsoft Windows.
TYPES OF SOCIAL MEDIA NETWORKS » Six distinct patterns of social networks are widely represented within Twitter, illustrating network patterns that are named to capture the specific kind of interaction that takes place within each network. See some examples on the following page. IN-GROUP: Few disconnected isolates and many connections POLARIZED: Two dense clusters with little interconnection BRAND/PUBLIC TOPIC: Many disconnected isolates and some small groups BAZAAR: Many medium-sized groups and some isolates BROADCAST: A hub that is retweeted by many different useres SUPPORT: A hub that replies to many disconnected users
Other SNA tools are web-based, and many pull data from social media users’ self-identified networks on websites like LinkedIn, Facebook, and Twitter. SNA can also be done offline with pencil and paper, using social mapping to identify actors, their connections, and power dynamics.
Limitations of online analysis Analysis using data pulled from the web can skew results, because the data only includes people and organizations that are online. For example, an analysis of data from Twitter would not show the reach of social actors who are not on Twitter, though they may have significant impact on a given group or topic. Similarly, offline analysis may miss subtle or hidden connections that are only apparent through the vast quantities of data available online.
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NodeXL and Twitter
Keywords in SNA
Using data from Twitter, NodeXL can show relationships between users, hashtags, words, and word pairs. Currently, Twitter allows NodeXL software to analyze the most recent seven-day period, including up to 10,000 tweets. The analysis can be centered on a specific user, hashtag, or a user’s last 10,000 tweets.
One way to analyze a social network is to look for the use and spread of key words. For example, the use of local language and slang can differentiate between local, regional, and international actors in events like the Arab Spring.
Network maps call out the key people at the center and points of connection between these groups, the “hubs” and “bridges” who play key roles in the population. Marc A. Smith Simple Network Analysis for Social Media
TYPES OF SOCIAL MEDIA NETWORK GRAPHS Âť
Few disconnected isolates, many connections
Many disconnected isolates, some small groups
A hub that is retweeted by many different users
Two dense clusters with little interconnection
Many medium-sized groups, some isolates
A hub that replies to many disconnected users
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SNA AND INTERNATIONAL DEVELOPMENT » • Analyze grantee relationships and status in communities to objectively rank their influence and outreach effectiveness • Mine hashtags to define different groups, optimize outreach activities, and bring each together around common concerns • Collaborate with social actors who can create influential advocacy campaigns • Expose and counteract fake social media accounts and manufactured attempts at grassroots movements • Find new business and employment connections for entrepreneurs and youth • Identify hidden disease vectors and stop new infection pathways
With the understanding that Twitter use is often concentrated in specific demographics, the use of words, word pairs, and hashtags in tweets can facilitate SNA by showing how key ideas are spread or repressed. The human identity is contingent on a person’s interactions and relationships. This explains why stereotypes arise that are inaccurate at the individual level, but often more accurate than desired at the aggregate level.
Social Network Analysis in International Development At its core, international development is about modifying beliefs and
behaviors to effect change in the human condition, which requires a keen understanding of who constituents know and who they will listen to. Understanding social networks can improve development work by providing tools to recognize key influencers and sub-groups in communities where we work, in order to target interventions to those who have the most social capital and impact potential. Additionally, social network analysis can be used internally within a development organization to map knowledge flows through employees and show actual workflows versus those represented in formal organizational charts.
SNA can also be used externally to improve development outcomes, for example to analyze grantee relationships and status in communities to objectively rank their influence and outreach effectiveness; or to mine hashtags to define different groups, optimize outreach activities, and bring each together around common concerns. For more information, visit www.irex. org and follow the IREX | Center for Collaborative Technology on Twitter at @IREXtech.
The IREX | Center for Collaborative Technology believes that technology facilitates access to vital information and news, strengthens engagement between citizens and government, informs a strong civil society, and underpins modern education. Learn more at www.irex.org.
IREXtech Explains are created through extensive conversations with international development practitioners, which seeks to explain challeng...