Vittel social media metrics - SentiCharts by SentiOne

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Vittel

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09/08 – 10/07

Vittel

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

Date	Mentions
Sep 8, 2025	0
Sep 9, 2025	1
Sep 10, 2025	0
Sep 11, 2025	0
Sep 12, 2025	1
Sep 13, 2025	0
Sep 14, 2025	3
Sep 15, 2025	0
Sep 16, 2025	1
Sep 17, 2025	0
Sep 18, 2025	0
Sep 19, 2025	0
Sep 20, 2025	1
Sep 21, 2025	0
Sep 22, 2025	0
Sep 23, 2025	1
Sep 24, 2025	15
Sep 25, 2025	2
Sep 26, 2025	0
Sep 27, 2025	0
Sep 28, 2025	0
Sep 29, 2025	1
Sep 30, 2025	1
Oct 1, 2025	0
Oct 2, 2025	1
Oct 3, 2025	1
Oct 4, 2025	1
Oct 5, 2025	1
Oct 6, 2025	1
Oct 7, 2025	0

09/08 – 10/07

Vittel

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

Sentiment	Mentions	Percent
positive	0	0%
negative	0	0%
neutral	2	100%
total	2	100%

09/08 – 10/07

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	30	93.75%
Instagram	1	3.13%
Twitter	1	3.13%

09/08 – 10/07

Vittel

Bad. The result is 0.00.
It seems your brand needs help. Order an in-depth report to understand your brand’s negative perception.

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

BHI
0.00

09/08 – 10/07

Vittel

09/08 – 10/07

Vittel

661 Total

0 Positive

0 Negative

370 Webpages

250 Social Media

Sources breakdown

– Blogs

– Forums

370 Websites

200 Instagram

– Facebook

– Video

– Reviews

50 Twitter

– TikTok

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

Sentiment	Reach
Positive	0
Negative	0
Total	661

Source	Reach
Webpages	370
Social Media	250
Total	661

Source	Reach
Blogs	–
Forums	–
Websites	370
Instagram	200
Facebook	–
Video	–
Reviews	–
Twitter	50
TikTok	–

09/08 – 10/07

Vittel

32 Total

0 Positive

0 Negative

45%Up

Sources breakdown

– Blogs

– Forums

30 Websites

1 Instagram

– Facebook

– Video

– Reviews

1 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.