I wanted to know what people actually say during an event, not what they say about it afterward.
Afterward is easy. Two days later the recap threads are up, the highlight clips are circulating, and a consensus has formed about what happened. That consensus is almost always wrong about the middle of the event, because the people who post recaps are not the same people who were posting at minute 34.
So I set up a search before a Real Madrid vs Barcelona Clásico and left it running. Then I did the same thing for a Coldplay night at Wembley Stadium in London. Two completely different crowds, two completely different vocabularies, and in both cases the interesting accounts were not the ones I would have found by searching afterward.
The reason is mechanical. To track tweets about an event in real time you need a search that collects forward from a moment you choose, accumulating posts as they appear. X's native search cannot do that. It shows you what exists right now, and refreshing it is not the same as collecting.
With Circleboom Twitter, you can set a start date, define the keywords, and let the Real-time Tweet Search tool gather matching public tweets from that point onward, including tweets posted after you set the search up, then flip the whole result into a deduplicated list of the accounts behind them.
What Is Circleboom Twitter?
Circleboom is an Official X Enterprise Developer, and the live collection described here runs on X's official Enterprise API.
No scraping, no browser extension sitting on your session. That matters for live event work specifically, because scraped live streams are exactly the kind of thing that breaks at the worst possible moment.
- Collects live public tweets forward from a start date you choose, including posts made after the search begins
- Captures full engagement metadata per tweet: impressions, likes, retweets, quotes, bookmarks, replies, and timestamp
- Pivots from the tweet list to a deduplicated profile view of every account that posted a match
- Filters the live stream by language, media type, hashtags, verified status, replies, links, and engagement minimums
- Exports either view to CSV, and stores the search under a log you can revisit without spending tokens again
That last point is the difference between watching an event and having a record of it.
How to Track Tweets About an Event in Real Time with Circleboom Twitter
- Connect your X account to Circleboom Twitter and open Real-time Tweet Search. Authentication runs through the official X Enterprise API, so no password is shared. The tool sits under Advanced X Search, and its positioning tells you what it does: find accounts from live tweets starting from a date.
- Describe the search in plain language. You do not need operator syntax to start. Write what you are looking for the way you would say it out loud, for example "posts about the Real Madrid Barcelona match tonight." Circleboom turns that into a structured query, shows the interpretation back to you as search summary chips, and offers AI refined variations you can accept or ignore.
- Open Filters and shape the query before you collect, not after. This is the step that decides whether your result is usable. The panel gives you keywords, keyword match type (exact phrase, contains, or partial), exclude terms, language, replies on or off, links on or off, hashtags, cashtags, verified accounts only, media type (all, images, videos, or text only), and engagement minimums and maximums. For a match, exclude replies and set a small engagement floor. For a concert, filter media type to video and leave the engagement floor off.
- Set the start date. Choose Last 24 Hours, Last 7 Days, Last 30 Days, or a custom date. For a scheduled event, custom is almost always the right answer, and setting it a few hours before the event start catches the pre event conversation where the real intent signals live. This is the setting that makes the search collect forward instead of querying a closed window in the past.
- Choose how many tweets to collect. This controls the collection size and the token cost, since each search consumes GetTweetTokens proportional to the volume. Note that this number does not equal the number of unique accounts you will get back, because one account can author many matching tweets. The remaining balance is shown during setup.
- Run the search and read the tweet view first. The results page reports how many tweets were collected for your keywords, in a table showing name, the post text with a link out to X, impressions, likes, retweets, quotes, bookmarks, replies, and the creation timestamp. Sort by timestamp to read the event chronologically, which is what native X search will not let you do.
- Click "Display Profiles of this search" to pivot to the accounts. This switches to a deduplicated list of every unique account behind those tweets, with follower count, following count, follow ratio, tweet count, join date, and an activity classification of Active, Moderate Active, or Inactive. Each account appears once no matter how many matching posts they made.
- Act while the window is still open. Per row you get follow or unfollow, whitelist, blacklist, and open profile. In bulk you get Follow, Auto Follow from the matching keyword, Unfollow, and an Add to List dropdown offering Twitter List, Mass Block List, Whitelist, or Blacklist. Set your quality filters before touching Auto Follow, because on a live keyword stream it keeps following every new match.
- Export both views before the conversation moves. Export is token based and separate from the search cost. Take the tweet view as your record of what was said and the profile view as your outreach or monitoring list. Live posts get deleted, edited, or made private within minutes, and engagement counts shift continuously.
- Revisit the search from the log later. Completed searches are stored and can be reopened without spending tokens again, which is what lets you compare one event against the next one without rebuilding the query from scratch.
What the Clásico Search Actually Turned Up
I set the start date to two hours before kickoff and ran the search on the fixture keywords plus both club hashtags, with replies excluded and a minimum engagement threshold applied so the stream would not fill with one word reactions.
The first thing that showed up was that the vocabulary changed three times during the match.
Before kickoff, the posts were predictions and lineup complaints. During the first half, they were almost entirely about the referee. After the second goal, the language shifted again to transfer speculation, which had nothing to do with the match in front of them. If I had searched the day after, I would have found only the third layer, because that is the conversation that survived. The first two had been buried under it.
The second thing was more useful. When I pivoted to the profile view, the accounts driving the referee conversation were not the big fan accounts. They were mid sized accounts, 3,000 to 20,000 followers, posting constantly during the window and getting quoted by larger accounts an hour later. The big accounts were amplifiers. These were sources.
📌 That distinction only exists in a live collection. Search the same keywords a week later and the mid sized accounts are invisible, because their posts were superseded and the quote tweets from the large accounts are what ranks.
I added the strongest thirty of them to an X List. Lists are the right container for this because they let you keep monitoring a group without following everyone and wrecking your own timeline, and you can bulk upload the handles from a CSV rather than adding them one at a time.
What the Concert Search Turned Up Instead
The Wembley show behaved nothing like the Clásico, and the difference is worth understanding before you set up your own search.
Football is a text event. People narrate it while watching. Concerts are a media event, and the posting volume is lower during the show and enormous in the ninety minutes afterward, when people upload the video they shot. If I had set the start date to the opening song and stopped collecting at the encore, I would have missed most of it.
So I set the start point earlier, at the afternoon before, and let it run overnight. That caught three separate phases: people posting about traffic and queues outside the venue, the sparse in show posts, and then the flood of clips afterward.
The media type filter did the heavy lifting here. Filtering to video only turned a noisy stream into a usable list of people who had actually filmed something, which is a completely different population than people who tweeted the setlist. For a brand or a venue trying to find usable content or people to work with, that filter is the entire workflow.
⚠️ One thing I did not expect: a meaningful share of the highest engagement posts during a concert are from accounts that were not there. Reaction posts, jokes, and reposted clips outperform the actual attendee footage. If you are building an attendee list, filter by engagement and you will get the wrong people. Filter by media type and location instead.
The social media listening angle is really what this is, applied to a two hour window instead of a quarter.
Why Native X Search Cannot Do This
X search queries what exists at the moment you press enter. There is no collection, no accumulation, and no persistence.
Practically, that means three things go wrong during a live event.
The stream moves faster than you can read it. A trending event generates posts faster than anyone can scroll, and the ranking you see is not chronological, so you cannot even be sure what you have and have not seen. Following a hashtag on X helps you watch, but watching is not capturing. The same limitation shows up whenever you try to track other people's activity on X without a collection layer underneath.
Posts disappear. Live tweets get deleted, edited, or made private within minutes. The post you saw at minute 12 may not exist at minute 40, and if you did not capture it, you have nothing. This is the single strongest argument for exporting early rather than at the end.
There is no account view. X gives you posts. Turning those posts into a list of people means opening profiles one at a time, which is impossible at live event pace. This is the same structural gap that makes account search on X and searching people on X frustrating in general, just compressed into a window where you have no time.
X's advanced search operators are genuinely good and worth knowing, but they query a static index. They do not collect forward. If your need is a live window, operators alone will not get you there, which is also why generic social media monitoring tools and apps for monitoring X activity vary so widely in what they can actually see.
Setting Up an Event Search That Does Not Drown You
A few things I would do differently, in order of how much they mattered.
Start earlier than the event. Pre event posting is where intent lives. People announce that they are going, ask about tickets, complain about logistics. That is a better prospect signal than anything posted during the event itself. Last 24 Hours, Last 7 Days, Last 30 Days, or a custom start date are all available, and for a scheduled event a custom start is almost always right.
Search the ugly keywords too. The official hashtag is the smallest part of the conversation. Venue name, city, opponent name, player names, support act, sponsor names, and the misspellings. During the Clásico, far more posts used "Madrid," "Barça," and the player surnames than the official #ElClasico tag, and a large share of them were in Spanish rather than English. Checking what is trending before you build the query is a cheap way to catch phrasing you would not have guessed, and it works even without a logged in account.
Exclude before you collect, not after. Exclude terms, language filters, and reply exclusion cost you nothing at setup and save an enormous amount of noise. Broad keywords during a live spike return large, low signal result sets very quickly.
Set an engagement minimum, but only for some goals. If you want the loudest voices, a minimum works. If you want attendees, it actively hurts you, because attendees post to their friends and get four likes. Match the filter to what you actually want. The metrics worth tracking are not the same for every question.
Export while it is running, not after. Live posts vanish. Engagement counts shift. Export the tweet view for the record and the profile view for the outreach list, and treat both as snapshots from the moment of retrieval.
Be careful with Auto Follow. Applying it to a live keyword stream will follow every matching account continuously, which during a trending event means following a lot of accounts you have not looked at. Set quality filters first, and remember that X caps how many accounts you can follow per day, roughly 50 to 400 depending on standing.
What You Lose by Doing This Afterward
The window closes. Engaging with someone about a match while the match is happening is normal. Doing it four days later is odd. The shared context is the permission structure, and it expires.
You only find the survivors. Retroactive search surfaces the posts that accumulated engagement, which systematically excludes the early, small, accurate ones. If you are trying to understand a conversation rather than its winners, that is a real distortion. Using X as a market research tool fails in exactly this way when the sample is drawn after the fact.
Crisis response becomes damage control. When the event is a problem rather than a party, the difference between hour one and day three is the whole outcome. How top brands use X for crisis management and protecting a reputation against viral negativity both come down to whether you were collecting before you needed to be.
You cannot tell a spike from a pattern. One live window on its own is not evidence of anything. Running the same keywords through historical tweet search tells you whether the spike is new or whether this happens at every Clásico. Old tweet search methods covers that side.
You post into the moment too late. The whole point of finding a live conversation is joining it. That means having something ready, which is a scheduling problem as much as a monitoring one. Live tweeting covers the practice, and knowing when your own followers are online determines whether your event posts land at all.
FAQ
Does it collect tweets posted after I set up the search?
Yes, and this is the core difference from historical search. Collection runs forward from your chosen start date, so posts made after you configure the search are included. Historical search queries a closed window in the past.
How far back can I set the start date?
Last 24 Hours, Last 7 Days, Last 30 Days, or a custom date. Setting it too far back effectively turns the search into a historical one and returns a less current result set than you probably intended.
Can I see the accounts, not just the posts?
Yes. The "Display Profiles of this search" button pivots to a deduplicated account view showing follower count, following count, follow ratio, tweet count, join date, and activity classification, with follow, list, whitelist, blacklist, and export actions. Each account appears once no matter how many matching tweets they posted.
How do I stop a trending hashtag from flooding the results?
Exclude terms, language filters, reply exclusion, media type, and engagement minimums, all set before collection rather than after. Start broad for a few minutes to learn the vocabulary people are actually using, then tighten. Trending hashtags on X and how many people saw my hashtag cover the volume side.
What if I only want to count a hashtag, not find accounts?
Then this is more tool than you need. The keyword and hashtag tracker handles counting directly, and there is a dedicated hashtag counter at https://circleboom.com/twitter-management-tool/twitter-search-tool/keyword-hashtag-tracker/twitter-hashtag-counter. For mentions of your own account specifically, use https://circleboom.com/twitter-management-tool/twitter-search-tool/twitter-advanced-search/track-twitter-mentions.
Are private accounts included?
No. Only public tweets from public accounts. Tweets deleted before the API indexed them will not appear, and tweets deleted after indexing may still show in results even though they are gone from X.
Does it cost anything to run?
Searches consume GetTweetTokens proportional to how many tweets you collect, and export consumes tokens separately. The balance is visible during setup. If the balance runs out mid collection, the search stops there and partial results are still saved. Saved searches can be revisited from the log without spending tokens again.
Can I use this for finding people to work with rather than monitoring?
Yes, and the profile view is built for it. Filter for the accounts posting real content during the window, then check them properly before reaching out. Finding X influencers step by step and finding influencers for your brand both apply, with the advantage that a live event list is pre qualified by actual participation rather than bio claims.
Final Thoughts
The Clásico and the concert taught me the same lesson from opposite directions. The conversation that survives an event is not the conversation that happened during it, and the accounts worth knowing are usually not the ones with the most followers.
You cannot recover any of that later. To track tweets about an event in real time you have to be collecting before the event starts, with the keywords set wide enough to catch how people actually talk and the filters set tight enough that you can still read the result.
With Circleboom Twitter, you can set the start date, collect live public tweets on X as they are posted, and turn the whole window into a list of accounts you can still reach while the moment is open.
