From 7f631c493d04ba96e36975365532e2172fec367e Mon Sep 17 00:00:00 2001 From: Mitja Felicijan Date: Thu, 7 Oct 2021 21:13:14 +0200 Subject: Added dithered images --- ...19-using-sentiment-analysis-for-click-bait-detection-in-rss-feeds.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'posts/2019-10-19-using-sentiment-analysis-for-click-bait-detection-in-rss-feeds.md') diff --git a/posts/2019-10-19-using-sentiment-analysis-for-click-bait-detection-in-rss-feeds.md b/posts/2019-10-19-using-sentiment-analysis-for-click-bait-detection-in-rss-feeds.md index c74501a..088b431 100644 --- a/posts/2019-10-19-using-sentiment-analysis-for-click-bait-detection-in-rss-feeds.md +++ b/posts/2019-10-19-using-sentiment-analysis-for-click-bait-detection-in-rss-feeds.md @@ -74,7 +74,7 @@ plt.show() 2. Rule-based approach may not be the best way of doing this. By using deep learning we would be able to get better insights. 3. **Next step would be to** periodically fetch RSS items and store them over a longer period of time and then perform analysis again and use either machine learning or deep learning on top of it. -![Relationship between title and description](/assets/sentiment-analysis/guardian-sa-title-desc-relationship.png) +![Relationship between title and description](/assets/sentiment-analysis/guardian-sa-title-desc-relationship.png.dith.gif) Figure above displays difference between title and description sentiment for specific RSS feed item. 1 means positive and -1 means negative sentiment. -- cgit v1.2.3