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Your Social Media Conversation Is Like A Topographic Map

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Your Social Media Conversation Is Like A Topographic Map
 
 

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Your Social Media Conversation Is Like A Topographic Map

Social media conversation is like a topographic map and the Pew Research Center is creating intense, visually-rich “maps” or charts to show you how. According to a new 57-page report entitled, Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters, Pew teamed up with the Social Media Research Foundation to help us understand conversations on Twitter.

Like topographic maps of mountain ranges, social network conversation maps can also illustrate the points on the landscape that have the highest elevation. These high points, in part, represent popular and widely repeated content, reflecting the significant role these people play in social media discussions.

Twitter users are only 18% of internet users and 14% of the overall adult population. Still, the structure of these Twitter conversations says something meaningful about how engaged users discuss topics, find each other, and share information.

Although this data from Pew revolves around Twitter, in the near future, some technology company is going to do the same with Facebook, or Google+, or Instagram and we’ll get another deep slice of how we communicate with one another on social media. The way that they did the analysis is itself interesting. By looking at things through the lens of social networks, they used new tools to examine the world. This data didn’t come from a survey or focus group, which is interesting.

In fact, this work reminds me of a great post from Matt Hixson at Tellagence: Using Social Market Research To Inform All Parts of Your Marketing. The title of Matt’s post says it all and is what Pew Research is also discovering.

Social media comes in different forms and structures. Mapping social media networks can enable a better understanding of the ways individuals form groups and organize online. I’ve pulled (and shortened) the following bullet points directly from the report, but the report itself includes the data visualizations:

  • Polarized Crowds often form around political topics
    • Why this matters: It underscores that partisan Twitter users rely on different information sources and commonly do not interact with those on the other side on Twitter.
  • Tight Crowds are shared spaces of learning and passion
    • Why this matters: These structures show how networked learning communities function and how sharing and mutual support can be facilitated by social media.
  • Brand Clusters are formed around products and celebrities
    • Why this matters: There are still institutions and topics that command mass interest but do not lead to the creation of connected conversations in a group.
  • Community Clusters are created around global news
    • Why this matters: Some information sources and subjects ignite multiple conversations, each cultivating its own audience and community. Community Clusters networks can reveal the diversity of opinion and perspective on a social media topic.
  • Broadcast Network structures are created when people re-tweet breaking news and commentary from pundits
    • Why this matters: Broadcast Network hubs are potent agenda setters and conversation starters in the new social media world. Enterprises and personalities with loyal followings can still have a large impact on the conversation.
  • Support Network conversations revolve around a singular source
    • Why this matters: As government, businesses, and groups increasingly provide services and support via social media, the support network structures becomes an important benchmark for evaluating the performance of these institutions.

The analysis and the maps of social structures were created using an open-source tool called NodeXL that is a plug-in to Excel spreadsheets. I just posted about another open source visualization tool called Plotly that lets you plug in data and stream it to the cloud for free. It is also a new social platform for people wanting to share their ideas visually and with the crowd. However, there are millions of people comfortable with Microsoft Excel who might find NodeXL perfect for solving a data challenge.

“These maps provide insights into people’s behavior in a way that complements and expands on traditional research methods such as public opinion surveys, focus groups, and even sentiment analysis of texts,” said Lee Rainie, Director of the Pew Research Center Internet Project. “It gives us a way to take the digital equivalent of aerial photos of crowds and simultaneously listen to their conversations.”

You can visit the full report here: Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters.

Source: Forbes

 

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<a href="/latest_stories/all/all/31" rel="author">Forbes</a>
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