From 234b763f49bfcc719c09acafdebf9eaf9d9783df Mon Sep 17 00:00:00 2001
From: johannawild <72805812+johannawild@users.noreply.github.com>
Date: Wed, 4 May 2022 00:44:04 +0200
Subject: [PATCH] Update README.md
---
README.md | 25 ++++++++++++++++++++++++-
1 file changed, 24 insertions(+), 1 deletion(-)
diff --git a/README.md b/README.md
index 46a8446..cee876b 100644
--- a/README.md
+++ b/README.md
@@ -97,7 +97,30 @@ Assume we want to plot the graph of top 20 occurring hashtags in the downloaded
The figure above shows the top 20 occurring hashtags among all the posts downloaded for the hashtag london. Clearly, the highest occurrence will be of the hashtag london as the file data/london/posts/data.json contain all the posts with hashtag london.
2. Printing the result in the shell: python3 hashtag_frequencies.py -d ../data/london/posts/data.json 20 -v
-
+
+```
+Rank Hashtag Occurrences Frequency (Occurrences/Total-Posts(total_posts))
+0 london 962 1.0
+1 fyp 493 0.5124740124740125
+2 uk 238 0.24740124740124741
+3 foryou 223 0.23180873180873182
+4 foryoupage 186 0.19334719334719336
+5 viral 177 0.183991683991684
+6 fypシ 85 0.08835758835758836
+7 funny 55 0.057172557172557176
+8 xyzbca 52 0.05405405405405406
+9 england 45 0.04677754677754678
+10 british 44 0.04573804573804574
+11 trending 39 0.04054054054054054
+12 fy 33 0.034303534303534305
+13 comedy 32 0.033264033264033266
+14 roadman 28 0.029106029106029108
+15 4u 27 0.028066528066528068
+16 usa 26 0.02702702702702703
+17 tiktok 26 0.02702702702702703
+18 travel 21 0.02182952182952183
+19 america 20 0.02079002079002079
+```
The same result of 1 is printed in the shell. The last column shows the ratio of the occurrence to the total posts.