Investigating Spikes in Social Media Conversations

Kimberly Surico |
 05/16/16 |
3 min read


Conversation spikes offer exceptional audience insight – and uncovering the information hidden within those spikes requires a little investigating. If you’re already using NetBase, this post will guide that thinking. And if you’re not using NetBase yet and would like to see this in action, reach out!

When you begin to analyze your topic, you’ll want to begin by understanding what, specifically is driving spikes for your Topic’s conversation. Doing this will help uncover trends, influential users in your conversation, and even clean your topic of any outliers or irrelevant conversations.



Step 1 – Understand if Sentiment is the Driver

In the Summary Metrics widget, select “Positives” and “Negatives” to be displayed on your Timeline.



You can see that the spike on February 14th was driven by posts with Positive Sentiment.

From there you would highlight the timeline to zoom in on February 14th and visit the Story Scope widget to uncover trending Positive conversations.









Step 2 – Understand if Influence is the Driver

Similar to Sentiment, add the Potential Impressions metric to the timeline to see if spikes are due to a large reach of users.


Once again, highlight to zoom in on each spike and visit the Authors widget. This will help you understand who might be involved in your conversation.

Zooming in on January 28th, we can see that the @BigSteveShow has contributed 391,867 impressions to the overall conversations.




@BigSteveShow has mentioned something about the brand’s CEO, so it may be good to follow up and investigate conversations around the term “CEO.” Chances are, if one influential user has involved his/herself in a conversation, other users (influential or otherwise) have as well.













Step 3 – Understand if a Source/Domain is the Driver

Sometimes Tumblr can be a large contributor to spikes in conversations (for example). Visit the Sources Widget and trend Sources over time to see if any spikes are driven by one Source over another.


In this example, the spike on February 14th is definitely driven by Twitter. But the Spike on February 18th is experiencing an influx of News posts.

Zooming in on that day and filtering by the one Source driving the conversation e.g. News, you can then visit any Conversation widget to uncover what is trending on that Source for the day.


This reveals the conversation on February 18th was driven by the brand’s fourth quarter earnings report:


Step 4 – Understand what Post Type is the Driver

Since NetBase can trend Post Type over time, add the three Post Types to the Summary Widget to understand what type of posts are driving conversation.


  • January 28th and February 14th are driven by Reposts
  • February 2nd, 9th, and 18th are driven by Original Posts
  • Replies remain consistent throughout

And when zooming in on February 2nd, add the Post Type filter for Original Posts.


And then we uncover the announcement that the brand is offering new direct flights to Hawaii as significant:








Additional Widgets to Uncover Trends

  • Popular Posts – Utilize this widget especially when working from a Firehose topic. This may present you with a direct answer as to which post is driving the spike in conversation.
  • Popular Links – Similar to the Popular Posts widget, you can see which links have the largest impressions, and may be an insight to what’s driving conversation.
  • Sentiment Drivers – Uncover user’s reactions to a conversation. Maybe users are expressing they want to “boycott” a brand, for example.

 And all of this combined (or separately, depending on need) can form the basis of a powerful influencer communication strategy, as it’s a rare case when brands aren’t surprised by what they find. Taking advantage of the audience insight available on Twitter and the many other platforms NetBase monitors is giving savvy brands an edge in even the noisiest niches. Check out some of our case studies to see some of what we’ve detailed here in action!

Image from Search Engine People Blog

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