Our platform stores and analyzes X (Twitter) data to provide you with valuable insights on the latest trends and help you stay up-to-date with the audience. Discover what's currently trending, track trend history(30 days), and explore popular hashtags and topics over the long term.
Here are the current top X (Twitter) trending topics United Kingdom, as of 4 minutes ago.
| Rank | Trending Topic / Hashtag | Tweet Volume | Copy |
|---|---|---|---|
| 1 | Heathrow
below 10k
|
below 10k | Copy |
| 2 | #ChineseGP
below 10k
|
below 10k | Copy |
| 3 | Penelope Keith
8.9k
|
8.9k | Copy |
| 4 | #WorldPoetryDay
12.8k
|
12.8k | Copy |
| 5 | #RedNoseDay
below 10k
|
below 10k | Copy |
| 6 | Eddie Jordan
23.4k
|
23.4k | Copy |
| 7 | #WorldDownSyndromeDay
below 10k
|
below 10k | Copy |
| 8 | #severance
87.1k
|
87.1k | Copy |
| 9 | Ezio
3k
|
3k | Copy |
| 10 | Littler
7.4k
|
7.4k | Copy |
| 11 | Frank
63.4k
|
63.4k | Copy |
| 12 | Ronaldo
121k
|
121k | Copy |
| 13 | Sol Campbell
2k
|
2k | Copy |
| 14 | Richard Bacon
2k
|
2k | Copy |
| 15 | Rob Cross
1.3k
|
1.3k | Copy |
| 16 | Southgate
3.2k
|
3.2k | Copy |
| 17 | Gatwick
1.9k
|
1.9k | Copy |
| 18 | Israel
963k
|
963k | Copy |
| 19 | Adolescence
49k
|
49k | Copy |
| 20 | Net Zero
below 10k
|
below 10k | Copy |
| 21 | Ravi
32.8k
|
32.8k | Copy |
| 22 | Hanley
below 10k
|
below 10k | Copy |
| 23 | Town Moor
below 10k
|
below 10k | Copy |
| 24 | Superdrug
below 10k
|
below 10k | Copy |
| 25 | Wordle 1,370 X
below 10k
|
below 10k | Copy |
| 26 | Tommy
163k
|
163k | Copy |
| 27 | Murrell
4.8k
|
4.8k | Copy |
| 28 | Gaza
803k
|
803k | Copy |
| 29 | Kirsty Coventry
21.7k
|
21.7k | Copy |
| 30 | Truman
154k
|
154k | Copy |
| 31 | Southport
13.2k
|
13.2k | Copy |
| 32 | Department of Education
417k
|
417k | Copy |
| 33 | Garron Noone
8.3k
|
8.3k | Copy |
| 34 | Tesla
1.3m
|
1.3m | Copy |
| 35 | Portugal
96.1k
|
96.1k | Copy |
| 36 | Hassan Nawaz
below 10k
|
below 10k | Copy |
| 37 | Edward Kenway
below 10k
|
below 10k | Copy |
| 38 | Suarez
17.6k
|
17.6k | Copy |
| 39 | Greece
16.6k
|
16.6k | Copy |
| 40 | Ralston
below 10k
|
below 10k | Copy |
| 41 | Lynx Africa
below 10k
|
below 10k | Copy |
| 42 | Bunting
1.4k
|
1.4k | Copy |
| 43 | Sturgeon
19k
|
19k | Copy |
| 44 | Jake Paul
3.1k
|
3.1k | Copy |
| 45 | World Cup
74.6k
|
74.6k | Copy |
| 46 | Happy Nowruz
17.4k
|
17.4k | Copy |
| 47 | MONA LISA
718k
|
718k | Copy |
| 48 | Steve McFadden
below 10k
|
below 10k | Copy |
| 49 | Panama
below 10k
|
below 10k | Copy |
| Note: Trends refreshes every Hour . to view the Hourly trending Trends for last 24 hour click of Expand view button below | |||
Get real-time updates on the hottest trending hashtags and topics on X (Twitter) United Kingdom with our automated page. Our page utilizes the official X (Twitter) API to refresh the most talked-about hashtags and topics every 30 minutes, ensuring you always have access to the most current trends on the platform.
These trending hashtags and topics are also popular on other social media platforms like Instagram, YouTube, and Facebook. Bookmark our page to stay updated on what's trending on X (Twitter) United Kingdom .
X (Twitter) uses a combination of factors to determine the most popular and relevant trending topics on the platform. These include the number of tweets, the number of users tweeting about a topic, and the level of engagement on tweets related to the topic. The platform's algorithms also consider the user's location and language to display trends that are relevant to their specific region and language.
Trending topics on X (Twitter) are not influenced by personal opinions or paid promotions, but rather reflect the interests and conversations of the X (Twitter) community as a whole. The platform's algorithms are designed to identify topics that are popular among a wide range of users, rather than just a small group. Any attempts to artificially manipulate trending topics are strictly prohibited by Twitter's policies.
X (Twitter) 's trending algorithm is designed to identify significant increases in the popularity of a specific topic or hashtag, compared to its usual level of activity. To do this, the algorithm takes into account both the volume of tweets about the topic (the number of tweets) and the time it takes to generate that volume of tweets. Time is a critical factor in determining trends, as a topic that gradually builds in popularity over the course of a month may generate a large number of tweets after 30 days, but may not have experienced a sudden spike in activity that would qualify it as a trend. By considering both volume and time, X (Twitter) 's trending algorithm is able to identify trends that are both popular and relevant to the current conversation on the platform.