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 New Orleans, as of 57 minutes ago.
Rank | Trending Topic / Hashtag | Tweet Volume | Copy |
---|---|---|---|
1 | Tennessee
76.1k
|
76.1k | Copy |
2 | Ohio State
48.9k
|
48.9k | Copy |
3 | Jeremiah Smith
below 10k
|
below 10k | Copy |
4 | Buckeyes
13.5k
|
13.5k | Copy |
5 | Clemson
51.7k
|
51.7k | Copy |
6 | Usyk
195.3k
|
195.3k | Copy |
7 | Ravens
80.5k
|
80.5k | Copy |
8 | Russ
24.9k
|
24.9k | Copy |
9 | Steelers
68.1k
|
68.1k | Copy |
10 | Ryan Day
below 10k
|
below 10k | Copy |
11 | Howard
20.7k
|
20.7k | Copy |
12 | #GoBucks
below 10k
|
below 10k | Copy |
13 | Lamar
53.3k
|
53.3k | Copy |
14 | #AEWCollision
below 10k
|
below 10k | Copy |
15 | Paige
14.9k
|
14.9k | Copy |
16 | Panama
44.7k
|
44.7k | Copy |
17 | UConn
below 10k
|
below 10k | Copy |
18 | #LAMH
below 10k
|
below 10k | Copy |
19 | #CFBPlayoff
35.9k
|
35.9k | Copy |
20 | Nico
68.1k
|
68.1k | Copy |
21 | Juju Watkins
below 10k
|
below 10k | Copy |
22 | Naylor
below 10k
|
below 10k | Copy |
23 | Rickey
99.3k
|
99.3k | Copy |
24 | Texas
146.5k
|
146.5k | Copy |
25 | Heupel
below 10k
|
below 10k | Copy |
26 | #HookEm
16.9k
|
16.9k | Copy |
27 | Tim Banks
below 10k
|
below 10k | Copy |
28 | The SEC
119.6k
|
119.6k | Copy |
29 | Derrick Henry
below 10k
|
below 10k | Copy |
30 | Jack Sawyer
below 10k
|
below 10k | Copy |
31 | Tomlin
below 10k
|
below 10k | Copy |
32 | Minkah
below 10k
|
below 10k | Copy |
33 | Chip Kelly
below 10k
|
below 10k | Copy |
34 | Columbus
20.1k
|
20.1k | Copy |
35 | Rocky Top
below 10k
|
below 10k | Copy |
36 | The Vols
13.3k
|
13.3k | Copy |
37 | Will Brooks
below 10k
|
below 10k | Copy |
38 | Marlon
14.6k
|
14.6k | Copy |
39 | Knoxville
below 10k
|
below 10k | Copy |
40 | Chiefs
123.9k
|
123.9k | Copy |
41 | Dabo
below 10k
|
below 10k | Copy |
42 | Kentucky
39.4k
|
39.4k | Copy |
43 | Santana
17.2k
|
17.2k | Copy |
44 | Jaydon Blue
below 10k
|
below 10k | Copy |
45 | Bateman
below 10k
|
below 10k | Copy |
46 | Howie
below 10k
|
below 10k | Copy |
47 | Indiana and SMU
17.7k
|
17.7k | Copy |
48 | Anthony Davis
below 10k
|
below 10k | Copy |
49 | Shoe
20.2k
|
20.2k | 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) New Orleans 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) New Orleans .
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.