06/10/2015
Mapping the Social Media Network: Target vs. Macy's
C2C, the connections among customers, is a powerful force in the world of B2C. People are talking to one another about retailers, products, brands, and services as much as they are listening to messages from brands and businesses themselves.
Social media has been a challenge for many brands: it is a vast blooming buzzing confusion of activity. But tools and methods from sociology and computer science are now able to bring social media streams into focus, revealing their structure, key people, key topics, and internal divisions.
Social media is inherently in the form of a network, it is made out of collections of connections. In aggregate, each like, link, reply, mention, follow, friend, and/or forward (among other kinds of connections), form a network. Networks are complex, but they can be analyzed using tools from math and computer science, informed by decades of sociological research. Social network analysis (SNA) is a powerful set of tools, theories and techniques for making sense of the webs of connection that form among people and groups. SNA is particularly well suited to understanding social media, where people are linked to people through communication. But until recently, SNA has been a complex tool limited to advanced data scientists and software developers.
Now, a free and open tool is available that makes social network analysis of social media about as hard as making a pie chart. The NodeXL application from the Social Media Research Foundation is an add-in for Excel that enables the simple collection, analysis, visualization, and reporting on streams of messages from a range of social media sources. Twitter, Facebook, YouTube, flickr, wikis, blogs, e-mail, and other forms of social media are all inherently networks, and they can now be quickly visualized and understood that way. Built inside the familiar Excel spreadsheet, the network overview discovery and exploration add-in simplifies the process of gaining network insights.
Network maps and reports highlight the overall shape and structure of a collection of connected people. The divisions or groups that define the neighborhoods or clusters in the network become clearly visible. Many networks are not a single structure, but rather a collection of sub-regions.
Within these structures a few people often stand out because they occupy rare and strategic locations. Some people are "hubs" with many people connecting to them who do not connect to one another. Others are isolates, connecting to no one. Another position is the bridge, linking two otherwise disconnected groups. In some cases people are part of communities, formed from dense webs of mutual connections.
These positions and shapes tell a story about the crowds that have gathered in social media around many topics, including brands, businesses, and products. For example, we can map the pattern of connection among the people who tweeted about Target and Macy's.
In these maps we can see several key structures: hub-and-spoke broadcasts and fragmented brand clusters. These shapes spotlight the role of the brand accounts (@macys and @target) that have attracted large circles of re-tweeters around them. In some cases, additional, smaller circles of connections are visible where "brand champions" have attracted their own audiences. The large block of rows of isolates, people who have zero connections, is an indicator of the brand visibility of these retailers. Ten to twenty percent of all the Twitter users who mentioned these brands never said anyone else's name nor did anyone ever say their name — they are peripheral, located at the edges of the discussion. These people are like islands waiting for someone to build a bridge between them and the brand by including them in the conversation. While most social media tools ignore these people at the margins, social network theory suggests that they are the most likely people for new customer acquisition. In contrast, the highly connected hubs, while influential, are likely to already be a customer and cannot be acquired again.
The shapes seen in these network maps are not the only forms that exist. In a recent research report published in collaboration with the Pew Research Internet Project, we documented the six basic forms of social media networks commonly found in many social media platforms. This research focused on Twitter, but it applies to many platforms that allow people to reply to one another. These six types of network patterns reveal the diversity of structures possible in social media.
Source: Pew Research Internet Project
This research showed that some networks formed a divided or polarized pattern, often related to political or controversial topics. But others lack these divisions, forming in-group communities where everyone seems to interact with nearly everyone. These dense patterns are not the only forms of social media network, however. Other topics, frequently related to brands and publicly visible topics, have a fragmented structure in which few people interact at all. Brands often have 40% to 50% of the people who mention them do so without mentioning the name of another person. These are the "isolates" — islands in the network containing just one person each. In a more mature form of the fragmented brand network, some connected groups can grow up alongside the confetti of disconnected people, often forming a collection of small clusters, each with its own audience and hub.
The final two patterns are mirrors of one another: the hub and spoke pattern where the arrows point inward or outward. These are the "broadcast" and "support" network types, created when a single account is the major focus of a large group who otherwise do not connect to one another. Hub-and-spoke broadcast networks feature a user who has attracted an audience who all re-tweet them but do not communicate with one another. In the "support" pattern, a single account replies to many otherwise disconnected people, offering to help resolve their customer issues.
Seen in this frame, we can now revisit the Macy's and Target network maps to see how they fit.
The Target network is composed of 5,551 Twitter users whose tweets in the requested range contained "@target OR #target", or who were replied to or mentioned in those tweets over the 4-day, 4-hour, 32-minute period from Friday, June 5, 2015 at 21:16 UTC to Wednesday, June 10, 2015 at 01:49 UTC.
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=46912
The top hashtags that co-occur with "Target" are #target, #toys, #jurassicworldattarget, #jurassicworld, #clothing, #disney, #giveaway, #newborn, #tees, #mplaces.
The most central people in the Target network are (ranked by network betweenness centrality): @target, @somethingidsay, @fbi, @mrsednajon, @imperfectwomen, @vadodimio, @carlste503, @big_daddy20000, @maintarun, @dawnchats.
The network is dominated by the "broadcast" cluster (G1) which is centered on the @Target account which is surrounded by re-tweeters who form a circle around it.
The next largest group in the network are the isolates, the collection of people who never said anyone else's name, nor did anyone in this discussion say their name. They are peripheral but could become more central if the brand and other brand champions engaged these critical but less visible contributors.
Additional clusters in this network also have broadcast hub-and-spoke patterns, suggesting that these accounts are brand champions, people who are both engaged with the brand and who have developed an active audience that re-tweets their messages. Engaging these brand champions is a critical strategy that can be guided by social media network insights. Network theory can quickly help identify the "mayors" of your topic network.
In contrast, compare this network of 3,442 Twitter users whose tweets in the requested range contained "macys", or who were replied to or mentioned in those tweets over the 4-day, 5-hour, 41-minute period from Friday, June 5, 2015 at 20:18 UTC to Wednesday, June 10, 2015 at 01:59 UTC.
Like Target, Macy's also has a big brand hub-and-spoke pattern, but, in contrast, it features a larger population of "isolates" — suggesting higher brand awareness for Macy's over Target. While the Target network is almost 40% larger than the Macy's network, Macys has a larger fraction of isolated participants (21% versus 10%). It has also attracted a handful of successful brand champions who have developed significant audiences of their own which responds to their mentions of Macys.
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=46911
The top hashtags that co-occur with "Macys" are: #job, #hiring, #makeup, #sales, #retail, #jobs, #sdcdadsday, #thaliasodicollection, #americanselfie, #macys
The most central people in the Macys network are (ranked by network betweenness centrality): @macys, @makeuptweeter, @macysbeautyjobs, @lbpyyz, @lta_inc, @carinkilbyclark, @thalia, @scm_guru, @gotyoursix, @slipnsliderazzi
The network is dominated by the "broadcast" cluster (G1) which is centered on the @macys account which is surrounded by re-tweeters who form a circle around it.
The next largest group in the network are the isolates, the peripheral users who could become more engaged.
Additional clusters in this network also have broadcast hub-and-spoke patterns, these are the people who are both engaged with the brand and who have developed an active audience that re-tweets their messages.
Tracking these maps, and the maps of related topics, brands, and retailers, can create a composite overview of the relevant parts of the social media landscape.
Both brands have promoted related hashtags, in this caseHere we see that "JurasicWorldAtTarget" has generated a single hub-and-spoke pattern, while the "americanselfie" network is multi-hubbed.
In some cases, it is useful to try to shift the pattern of network from one form to another to create a structure that is optimized for particular business goals. Communities often dream of becoming brands, while brands often seek to grow their communities.
Network metrics are therefore useful "KPIs" for tracking the structure as well as the volume of social media activity.
Networks are a powerful way of thinking about markets and consumer conversations. New tools are making network analysis as easy as making a pie chart. The result is an expansion of "network consciousness" as business decision makers are increasingly able to "think link" when they look at social media and market data.
Interested in seeing what your brand's social media network looks like? Request a free sample network map and report from http://connectedaction.net
Marc Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. Smith leads the Connected Action consulting group and lives and works in Silicon Valley, CA. Smith co-founded and directs the Social Media Research Foundation, a non-profit devoted to open tools, data, and scholarship related to social media research.
Editor's Note: If you are going to the Retail Executive Summit, June 17-19, be sure to Tweet about the event with hashtag #2015RES. The most influential Tweeter will receive a $100 gift card and be named the "Social Media Mayor" of the event.
Social media has been a challenge for many brands: it is a vast blooming buzzing confusion of activity. But tools and methods from sociology and computer science are now able to bring social media streams into focus, revealing their structure, key people, key topics, and internal divisions.
Social media is inherently in the form of a network, it is made out of collections of connections. In aggregate, each like, link, reply, mention, follow, friend, and/or forward (among other kinds of connections), form a network. Networks are complex, but they can be analyzed using tools from math and computer science, informed by decades of sociological research. Social network analysis (SNA) is a powerful set of tools, theories and techniques for making sense of the webs of connection that form among people and groups. SNA is particularly well suited to understanding social media, where people are linked to people through communication. But until recently, SNA has been a complex tool limited to advanced data scientists and software developers.
Now, a free and open tool is available that makes social network analysis of social media about as hard as making a pie chart. The NodeXL application from the Social Media Research Foundation is an add-in for Excel that enables the simple collection, analysis, visualization, and reporting on streams of messages from a range of social media sources. Twitter, Facebook, YouTube, flickr, wikis, blogs, e-mail, and other forms of social media are all inherently networks, and they can now be quickly visualized and understood that way. Built inside the familiar Excel spreadsheet, the network overview discovery and exploration add-in simplifies the process of gaining network insights.
Network maps and reports highlight the overall shape and structure of a collection of connected people. The divisions or groups that define the neighborhoods or clusters in the network become clearly visible. Many networks are not a single structure, but rather a collection of sub-regions.
Within these structures a few people often stand out because they occupy rare and strategic locations. Some people are "hubs" with many people connecting to them who do not connect to one another. Others are isolates, connecting to no one. Another position is the bridge, linking two otherwise disconnected groups. In some cases people are part of communities, formed from dense webs of mutual connections.
These positions and shapes tell a story about the crowds that have gathered in social media around many topics, including brands, businesses, and products. For example, we can map the pattern of connection among the people who tweeted about Target and Macy's.
In these maps we can see several key structures: hub-and-spoke broadcasts and fragmented brand clusters. These shapes spotlight the role of the brand accounts (@macys and @target) that have attracted large circles of re-tweeters around them. In some cases, additional, smaller circles of connections are visible where "brand champions" have attracted their own audiences. The large block of rows of isolates, people who have zero connections, is an indicator of the brand visibility of these retailers. Ten to twenty percent of all the Twitter users who mentioned these brands never said anyone else's name nor did anyone ever say their name — they are peripheral, located at the edges of the discussion. These people are like islands waiting for someone to build a bridge between them and the brand by including them in the conversation. While most social media tools ignore these people at the margins, social network theory suggests that they are the most likely people for new customer acquisition. In contrast, the highly connected hubs, while influential, are likely to already be a customer and cannot be acquired again.
The shapes seen in these network maps are not the only forms that exist. In a recent research report published in collaboration with the Pew Research Internet Project, we documented the six basic forms of social media networks commonly found in many social media platforms. This research focused on Twitter, but it applies to many platforms that allow people to reply to one another. These six types of network patterns reveal the diversity of structures possible in social media.
Source: Pew Research Internet Project
This research showed that some networks formed a divided or polarized pattern, often related to political or controversial topics. But others lack these divisions, forming in-group communities where everyone seems to interact with nearly everyone. These dense patterns are not the only forms of social media network, however. Other topics, frequently related to brands and publicly visible topics, have a fragmented structure in which few people interact at all. Brands often have 40% to 50% of the people who mention them do so without mentioning the name of another person. These are the "isolates" — islands in the network containing just one person each. In a more mature form of the fragmented brand network, some connected groups can grow up alongside the confetti of disconnected people, often forming a collection of small clusters, each with its own audience and hub.
The final two patterns are mirrors of one another: the hub and spoke pattern where the arrows point inward or outward. These are the "broadcast" and "support" network types, created when a single account is the major focus of a large group who otherwise do not connect to one another. Hub-and-spoke broadcast networks feature a user who has attracted an audience who all re-tweet them but do not communicate with one another. In the "support" pattern, a single account replies to many otherwise disconnected people, offering to help resolve their customer issues.
Seen in this frame, we can now revisit the Macy's and Target network maps to see how they fit.
The Target network is composed of 5,551 Twitter users whose tweets in the requested range contained "@target OR #target", or who were replied to or mentioned in those tweets over the 4-day, 4-hour, 32-minute period from Friday, June 5, 2015 at 21:16 UTC to Wednesday, June 10, 2015 at 01:49 UTC.
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=46912
The top hashtags that co-occur with "Target" are #target, #toys, #jurassicworldattarget, #jurassicworld, #clothing, #disney, #giveaway, #newborn, #tees, #mplaces.
The most central people in the Target network are (ranked by network betweenness centrality): @target, @somethingidsay, @fbi, @mrsednajon, @imperfectwomen, @vadodimio, @carlste503, @big_daddy20000, @maintarun, @dawnchats.
The network is dominated by the "broadcast" cluster (G1) which is centered on the @Target account which is surrounded by re-tweeters who form a circle around it.
The next largest group in the network are the isolates, the collection of people who never said anyone else's name, nor did anyone in this discussion say their name. They are peripheral but could become more central if the brand and other brand champions engaged these critical but less visible contributors.
Additional clusters in this network also have broadcast hub-and-spoke patterns, suggesting that these accounts are brand champions, people who are both engaged with the brand and who have developed an active audience that re-tweets their messages. Engaging these brand champions is a critical strategy that can be guided by social media network insights. Network theory can quickly help identify the "mayors" of your topic network.
In contrast, compare this network of 3,442 Twitter users whose tweets in the requested range contained "macys", or who were replied to or mentioned in those tweets over the 4-day, 5-hour, 41-minute period from Friday, June 5, 2015 at 20:18 UTC to Wednesday, June 10, 2015 at 01:59 UTC.
Like Target, Macy's also has a big brand hub-and-spoke pattern, but, in contrast, it features a larger population of "isolates" — suggesting higher brand awareness for Macy's over Target. While the Target network is almost 40% larger than the Macy's network, Macys has a larger fraction of isolated participants (21% versus 10%). It has also attracted a handful of successful brand champions who have developed significant audiences of their own which responds to their mentions of Macys.
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=46911
The top hashtags that co-occur with "Macys" are: #job, #hiring, #makeup, #sales, #retail, #jobs, #sdcdadsday, #thaliasodicollection, #americanselfie, #macys
The most central people in the Macys network are (ranked by network betweenness centrality): @macys, @makeuptweeter, @macysbeautyjobs, @lbpyyz, @lta_inc, @carinkilbyclark, @thalia, @scm_guru, @gotyoursix, @slipnsliderazzi
The network is dominated by the "broadcast" cluster (G1) which is centered on the @macys account which is surrounded by re-tweeters who form a circle around it.
The next largest group in the network are the isolates, the peripheral users who could become more engaged.
Additional clusters in this network also have broadcast hub-and-spoke patterns, these are the people who are both engaged with the brand and who have developed an active audience that re-tweets their messages.
Tracking these maps, and the maps of related topics, brands, and retailers, can create a composite overview of the relevant parts of the social media landscape.
Both brands have promoted related hashtags, in this caseHere we see that "JurasicWorldAtTarget" has generated a single hub-and-spoke pattern, while the "americanselfie" network is multi-hubbed.
In some cases, it is useful to try to shift the pattern of network from one form to another to create a structure that is optimized for particular business goals. Communities often dream of becoming brands, while brands often seek to grow their communities.
Network metrics are therefore useful "KPIs" for tracking the structure as well as the volume of social media activity.
Networks are a powerful way of thinking about markets and consumer conversations. New tools are making network analysis as easy as making a pie chart. The result is an expansion of "network consciousness" as business decision makers are increasingly able to "think link" when they look at social media and market data.
Interested in seeing what your brand's social media network looks like? Request a free sample network map and report from http://connectedaction.net
Marc Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. Smith leads the Connected Action consulting group and lives and works in Silicon Valley, CA. Smith co-founded and directs the Social Media Research Foundation, a non-profit devoted to open tools, data, and scholarship related to social media research.
Editor's Note: If you are going to the Retail Executive Summit, June 17-19, be sure to Tweet about the event with hashtag #2015RES. The most influential Tweeter will receive a $100 gift card and be named the "Social Media Mayor" of the event.
