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 Denmark, as of 15 minutes ago.
| Rank | Trending Topic / Hashtag | Tweet Volume | Copy |
|---|---|---|---|
| 1 | Arla
1.4k
|
1.4k | Copy |
| 2 | #obdk
below 10k
|
below 10k | Copy |
| 3 | Tesla
168k
|
168k | Copy |
| 4 | Andreas
30.2k
|
30.2k | Copy |
| 5 | #KingRezaPahlavi
52.5k
|
52.5k | Copy |
| 6 | christian poulsen
below 10k
|
below 10k | Copy |
| 7 | Bybit
336k
|
336k | Copy |
| 8 | Model Y
6.4k
|
6.4k | Copy |
| 9 | Apple
536k
|
536k | Copy |
| 10 | Chelsea
63.2k
|
63.2k | Copy |
| 11 | Elon
1.6m
|
1.6m | Copy |
| 12 | Mona
31.7k
|
31.7k | Copy |
| 13 | #에이티즈
62.5k
|
62.5k | Copy |
| 14 | Putinist
below 10k
|
below 10k | Copy |
| 15 | Lyngby
below 10k
|
below 10k | Copy |
| 16 | #JHOPE
233k
|
233k | Copy |
| 17 | mads bech
below 10k
|
below 10k | Copy |
| 18 | Bond
81.4k
|
81.4k | Copy |
| 19 | #dkøko
below 10k
|
below 10k | Copy |
| 20 | Gode
1.9k
|
1.9k | Copy |
| 21 | Vejle
below 10k
|
below 10k | Copy |
| 22 | Farum
below 10k
|
below 10k | Copy |
| 23 | Epstein
350k
|
350k | Copy |
| 24 | SpaceX
78.4k
|
78.4k | Copy |
| 25 | Bovaer
1.1k
|
1.1k | Copy |
| 26 | Ukraine
1.2m
|
1.2m | Copy |
| 27 | Zelensky
509k
|
509k | Copy |
| 28 | NASA
82.6k
|
82.6k | Copy |
| 29 | Astralis
below 10k
|
below 10k | Copy |
| 30 | Messi
77.1k
|
77.1k | Copy |
| 31 | israelske
below 10k
|
below 10k | Copy |
| 32 | Sociedad
81k
|
81k | Copy |
| 33 | Ungarn
5.9k
|
5.9k | Copy |
| 34 | Clara Tauson
below 10k
|
below 10k | Copy |
| 35 | Hamas
936k
|
936k | Copy |
| 36 | Moderaterne
below 10k
|
below 10k | Copy |
| 37 | Iran
116k
|
116k | Copy |
| 38 | Heidenheim
below 10k
|
below 10k | Copy |
| 39 | Morten
below 10k
|
below 10k | Copy |
| 40 | Russian
266k
|
266k | Copy |
| 41 | Ukrainians
90.1k
|
90.1k | Copy |
| 42 | Masha
8.9k
|
8.9k | Copy |
| 43 | Grok
339k
|
339k | Copy |
| 44 | Jamen
below 10k
|
below 10k | Copy |
| 45 | Hillerød
below 10k
|
below 10k | Copy |
| 46 | Tænker
1.1k
|
1.1k | Copy |
| 47 | Vestbredden
below 10k
|
below 10k | Copy |
| 48 | Pelle
2.7k
|
2.7k | Copy |
| 49 | København
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) Denmark 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) Denmark .
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.