Talent Monitoring With Social Listening Data

Over the past year, one of the fastest-growing use cases for bulk social listening analytics has been talent management companies leveraging social listening APIs to track talent across multiple platforms with greater flexibility. These agencies specialize in managing and advising influencers, athletes, actors, politicians, and other public figures with large social followings. Some talent agencies use web apps to do this - this works well if you have a non-technical team or just a few influencers you need to monitor. However, social listening APIs shine when the number you need to manage scales up.

Web applications quickly become impractical when analyst teams need to oversee thousands of queries across multiple divisions. This is where social listening APIs, like Infegy’s, make a difference. Infegy’s API, consistently ranked as the best in the industry, provides the scale and speed necessary to track and analyze talent efficiently. Let’s walk you through the process so your agency’s data science team can do the same!

Tracking Influencers Within A Social Listening Platform

Let’s start with a simple use case. Say you need to track just a few public figures across social media. Infegy Starscape provides a powerful, no-code solution to monitor real-time conversations, trends, and sentiment. Unlike API-based approaches that require technical expertise, Infegy Starscape offers an intuitive web-based platform where users can customize and refine their searches without writing a single line of code. Whether you’re tracking athletes, influencers, or executives, you can easily adjust search parameters, filter results, and visualize insights.

^{Figure 1: Post Volume Across 4 Influential Sports Figures (November 24, 2024 through February 23, 2025); 
Infegy Social Dataset}

Figure 1 shows post volume for four of the largest figures in international sports (you can also query the specific talent that you’re interested in). You’ll note a big surge in post volume for Ronaldo in early February—that was for his 40th birthday, which attracted a deluge of content pieces talking about his legacy.  

Using web tools, we can go further than post volume. Infegy Starscape allows you to chart other metrics generated by Infegy AI, like Anticipation. Figure 2 shows how Anticipation for Tom Brady rose the week before the Super Bowl, his first week commentating on Fox. That surge dropped quickly after the Super Bowl ended, which also coincided with our experience.

^{Figure 2: Count of Anticipation Across 4 Influential Sports Figures (November 24, 2024 through February 23, 2025); Infegy Social Dataset.}

Tracking Influencers With Flexible API Tools

Using out-of-the-box social listening tools scales well, especially if you’re in the data exploration phase and you don’t want to involve engineering teams. However, say you need to monitor a flexible, dynamic list of hundreds (or thousands) of potential influencers or talent. Pretty quickly, using frontend tools requires too much manual effort. For that, we’ll leverage Infegy’s powerful API.

We'll start with a specific portfolio of influencers we want to track, organizing them in a shareable Google Sheets spreadsheet for the sake of this blog. Ideally, you’d use a database with built-in controls like version tracking, concurrency protection, and approval workflows. The key is maintaining a centralized repository of influencers—this serves as a single source of truth for analysts and talent agents, helping to prevent the fragmentation issues mentioned earlier.

^{Figure 3: First Five Rows Of Our Influencer Dataset We Generated With A Large Language Model
(Link to full dataset).}

Your team can easily add or remove influencers and talent from each category as needed. A major advantage of programmatic social listening is the flexibility to modify categories dynamically. For example, if you decide to start monitoring fine artists, simply add another column. When our program runs, it will automatically create a new section in the output dedicated to that category.

Building Programmatic Queries At Scale

Next, we’ll walk you through how to build social listening queries at scale. Traditionally, constructing queries and waiting for results is the most labor-intensive part of any social listening practice. This process becomes exponentially more challenging as you add more queries. However, with tools like Infegy Starscape, you can build queries programmatically, streamlining the process. We use programmatic query-building regularly—it powers Infegy’s dashboards and our recent research analyzing hundreds of older Super Bowl commercials.

^{Figure 4: Programmatic Query For Talent Tracking Across Multiple Platforms}

To build a programmatic query in this case, we’ll first define our schema. For this example, we’ll keep it simple—using just a Boolean block and a relative lookback over the past year—but Infegy’s modular query structure allows for queries of any complexity. For instance, when analyzing movie trailers, we accounted for multiple versions by applying dynamic date filters based on the number of trailers released for each film.

To construct a sample query term, we’ll use Boolean logic by inserting AND between each word of a person's name. For example, the code in Figure 4 would transform the search term "Robert Downey Jr." into Robert AND Downey AND Jr. Programmatic query-building can be as simple or advanced as needed. Another effective approach for tracking talent is injecting their specific social media handles across multiple platforms to ensure comprehensive coverage of relevant mentions. We also could use content subject filters (like excluding promotional content) to ensure that we get clean results.

^{Figure 5: Sample boolean query construction}

Finally, we’ll loop through each term in our mock dataset that we created in Figure 1, and send each of these queries to Infegy’s API for results.

The Results

We ran our script and obtained our results. By default, we looked at volume, sentiment, and the top words associated with each one of our sports figures. Let’s briefly look at our results.

Volume By Industry

Post volume is a key metric for talent agencies, as it helps gauge an influencer's cost and impact based on the size of their online presence. Figure 5 displays the daily post volume breakdown for each influencer over the past year, using the well-known Plotly library for visualization.

Notably, Figure 5 reveals predictable spikes in activity—for example, Simone Biles and Novak Djokovic saw significant increases in mentions around the 2024 Paris Olympics

^{Figure 6: Volume-Based Results For The Athletic Talent We Tracked Via Infegy Starscape’s API (February 2024 through February 2025); Infegy Social Dataset}

We see similar trends when tracking politicians from the spreadsheet. Ahead of the November 2024 election, mentions of Donald Trump and Kamala Harris surge. Meanwhile, Justin Trudeau experienced a spike in late January 2025, coinciding with the tariff conflict between the U.S. and Canada.

^{Figure 7: Volume-Based Results For The Politicians We Tracked Via Infegy Starscape’s API (February 2024 through February 2025); Infegy Social Dataset}

Sentiment By Industry

If you're tracking high-profile talent, volume alone isn't enough. At Infegy, we respectfully disagree with the saying, "All publicity is good publicity." (If you don’t believe us, just check out our Brand Risk Dashboard—trust us, you don’t want to end up on that list.)

To gain deeper insights into the nature of conversations, you can analyze net positive sentiment. Figure 7 displays weekly net sentiment for selected movie stars, including Scarlett Johansson, Leonardo DiCaprio, and Chris Hemsworth. (Note: We’ve highlighted only a few celebrities to keep the chart readable—sentiment fluctuates so much that including too many names would create a messy, unreadable “spaghetti chart.”)

You'll notice a dip in sentiment for Johansson around May 2024, coinciding with OpenAI’s controversy over using a voice resembling hers. Similarly, DiCaprio’s sentiment declined in September 2024 amid rumors linking him to Sean Combs’ alleged illegal parties.

^{Figure 8: Sentiment-Based Results For The Movie Stars We Tracked Via Infegy Starscape’s API (February 2024 through February 2025); Infegy Social Dataset.}

JSON Based Outputs To Move Data Where You Need It

We’ve covered the analysis results—volume, sentiment, and much more if you dive into Infegy’s API. But we haven’t yet discussed the most critical aspect of using a social listening API: data portability.

When relying on web-based platforms to analyze social datasets, exporting the data you need into the right application can be challenging. Infegy’s API solves this by making data extraction seamless. You can define the specific format (JSON, CSV) and schema (keys, values, and arrays) required for your application. This flexibility allows you to integrate social data where it has the most impact—whether that’s an off-the-shelf visualization tool like Tableau or Power BI or a fully customized full-stack web application.

^{Figure 9: Customized Format For JSON Output}

Takeaways For Your Social Listening Practice

Talent agencies need more than basic insights—they need scalable, flexible tracking for thousands of public figures. Infegy’s API streamlines large-scale monitoring with deep sentiment and volume analysis, helping agencies stay ahead of trends and risks. With seamless integration into dashboards, BI tools, and custom applications, social intelligence becomes an actionable, real-time advantage.

If you'd like to see the script we used for this analysis or learn how to integrate social data into your talent management workflow, schedule a conversation with us here.

Key Ideas

• Scalable Tracking: Infegy's API automates the monitoring of thousands of talent profiles across platforms.
• Sentiment Insights: Track sentiment to manage risks and spot trends in real time.
• Easy Integration: Export data seamlessly into dashboards, BI tools, or custom apps.