Vittel social media metrics - SentiCharts by SentiOne

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Vittel

Beverages

#28

1.00

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09/22 – 10/21

Vittel

Shows the number of mentions a topic has received over time.

Date	Mentions
Sep 22, 2024	0
Sep 23, 2024	1
Sep 24, 2024	1
Sep 25, 2024	2
Sep 26, 2024	1
Sep 27, 2024	1
Sep 28, 2024	1
Sep 29, 2024	0
Sep 30, 2024	3
Oct 1, 2024	0
Oct 2, 2024	0
Oct 3, 2024	0
Oct 4, 2024	0
Oct 5, 2024	1
Oct 6, 2024	2
Oct 7, 2024	0
Oct 8, 2024	1
Oct 9, 2024	2
Oct 10, 2024	0
Oct 11, 2024	1
Oct 12, 2024	2
Oct 13, 2024	2
Oct 14, 2024	1
Oct 15, 2024	3
Oct 16, 2024	1
Oct 17, 2024	2
Oct 18, 2024	0
Oct 19, 2024	1
Oct 20, 2024	0
Oct 21, 2024	0

09/22 – 10/21

Vittel

Shows all of the mentions divided by sentiment: positive, neutral, negative.

Sentiment	Mentions	Percent
positive	2	20%
negative	0	0%
neutral	8	80%
total	10	100%

09/22 – 10/21

Vittel

Shows the ratio between source types for a given project. The source types are as follows: Facebook, Instagram, video, Twitter, blogs, websites, reviews, forums.

Source	Mentions	Percent
Websites	19	65.52%
Twitter	10	34.48%

09/22 – 10/21

Vittel

Excellent! The result is 1.00.
Well done! Your brand is loved on the internet!

Shows the ratio of positive to negative statements in a given time period.

BHI
1.00

09/22 – 10/21

Vittel

09/22 – 10/21

Vittel

~ 24 k Total

~ 10 k Positive

0 Negative

~ 9 k Webpages

~ 16 k Social Media

Sources breakdown

– Blogs

– Forums

~ 9 k Websites

– Instagram

– Facebook

– Video

– Reviews

~ 16 k Twitter

– TikTok

Displays the reach of all results found within a given project, divided by sentiment and sources.

Sentiment	Reach
Positive	10000
Negative	0
Total	24472

Source	Reach
Webpages	8803
Social Media	15669
Total	24472

Source	Reach
Blogs	–
Forums	–
Websites	8803
Instagram	–
Facebook	–
Video	–
Reviews	–
Twitter	15669
TikTok	–

09/22 – 10/21

Vittel

29 Total

2 Positive

0 Negative

69%Down

100%Up

Sources breakdown

– Blogs

– Forums

19 Websites

– Instagram

– Facebook

– Video

– Reviews

10 Twitter

– TikTok

An overview of all of the results found for a given project. Aside from showing the total number of mentions, their sentiment, and their source share, it shows how the results have shifted compared to the previous period. Sentiment detection is based on the proprietary algorithm provided by SentiOne.