diff --git a/Makefile b/Makefile
index 86067a6..abaa488 100644
--- a/Makefile
+++ b/Makefile
@@ -17,6 +17,8 @@ serve:
clean:
rm -rf site .env
+check: lint
+
lint:
docker run --rm -v "$$(pwd):/workdir" davidanson/markdownlint-cli2:latest
diff --git a/docs/assets/screenshots/portal/apollo-news_sentiments.png b/docs/assets/screenshots/portal/apollo-news_sentiments.png
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deleted file mode 100644
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diff --git a/docs/assets/screenshots/tagesschau/tagesschau-article2-expanded.png b/docs/assets/screenshots/tagesschau/tagesschau-article2-expanded.png
deleted file mode 100644
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diff --git a/docs/assets/screenshots/tagesschau/tagesschau-portal.jpg b/docs/assets/screenshots/tagesschau/tagesschau-portal.jpg
deleted file mode 100644
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diff --git a/docs/de/index.md b/docs/de/index.md
index 8dc9f68..43c3d4b 100644
--- a/docs/de/index.md
+++ b/docs/de/index.md
@@ -10,7 +10,7 @@ Der „News Deframer“ ist ein sprachliches Analysetool für Ihre bevorzugten N
* Wir [ersetzen](showcases/index.md) die Portalseite.
* Jede Schlagzeile wird in neutrale Sprache überführt (Reduktion von Clickbait, Reizüberflutung, Suggestion und Framing).
-* Integrierte [Trendanalyse](trends/index.md) zur Erkennung von Talking Points.
+* Integrierte [Trendanalyse](trends/index.md) zur Erkennung von Talking Points und [Sentiments](sentiments/index.md) Visualisierung.
* Vergleich verschiedener Nachrichtenportale, z. B. "Tagesschau" mit "Apollo News" oder "Bild" mit dem "Bayerischen Rundfunk".
* Per Klick gelangen Sie zurück zum Originalartikel bzw. zur ursprünglichen Portalseite.
diff --git a/docs/de/links.md b/docs/de/links.md
index 077f13c..3d39572 100644
--- a/docs/de/links.md
+++ b/docs/de/links.md
@@ -5,6 +5,8 @@
- [Quellcode](https://github.com/deframer/news-deframer/)
- [Quellcode Trend Mining](https://github.com/deframer/news-deframer-mining/)
- [Fehler melden](https://github.com/deframer/news-deframer/issues)
+- [MEmoLon – The Multilingual Emotion Lexicon](https://github.com/JULIELab/MEmoLon)
+- [Parquet Dateien für MEmoLon](https://github.com/deframer/memolon-parquet/)
- [Lizenz](license.md)
## Kontakt
diff --git a/docs/de/mobile-app/index.md b/docs/de/mobile-app/index.md
new file mode 100644
index 0000000..aaeefb5
--- /dev/null
+++ b/docs/de/mobile-app/index.md
@@ -0,0 +1,3 @@
+# Mobile App
+
+Demnächst verfügbar.
diff --git a/docs/de/sentiments/index.md b/docs/de/sentiments/index.md
new file mode 100644
index 0000000..cecf611
--- /dev/null
+++ b/docs/de/sentiments/index.md
@@ -0,0 +1,12 @@
+# Sentiments
+
+
+
+* **Sentiments**: Zeigt die emotionalen Werte der ausgewählten Artikel basierend auf lexikalischen Schätzungen.
+* **Original vs. Deframed**: Wechseln Sie zwischen den ursprünglichen Artikeltexten aus dem RSS-Feed und den deframten Versionen, um die vom News Deframer entfernte emotionale Wirkung zu visualisieren.
+
+## Warum Sentiments?
+
+Wir verwenden einen VAD/VAC (Dimensional) und BE5 (Diskret) Ansatz zur Erkennung von Stimmungen und Emotionen in Texten. Dabei nutzen wir die Sentiment-Werte von [MEmoLon](https://github.com/JULIELab/MEmoLon), einem Emotionslexikon für über 90 Sprachen. Das **VAD**-Modell (Valenz, Arousal/Erregung, Dominanz) bewertet die allgemeine Stimmung auf einer Skala von 1-9 in den Bereichen Valenz (Polarität/Angenehmheit), Arousal (Aktivierung/Erregung) und Dominanz (wahrgenommene Kontrolle). Das **BE5**-Modell misst die Intensität der diskreten Emotionen – Freude, Wut, Traurigkeit, Angst und Ekel – auf einer Skala von 1-5.
+
+Es gibt grundlegende wissenschaftliche Erkenntnisse, die diese Methodik stützen: fMRT-Experimente zeigen, dass das Lesen bestimmter Wörter tatsächlich messbare emotionale Reaktionen im Gehirn hervorrufen kann. Weitere Details zu dieser Theorie finden Sie in dieser [Dissertation](https://edoc.ub.uni-muenchen.de/18933/1/Danner_Sandro_C.pdf).
diff --git a/docs/en/index.md b/docs/en/index.md
index 1a86c1e..642f8ba 100644
--- a/docs/en/index.md
+++ b/docs/en/index.md
@@ -15,7 +15,7 @@ News Deframer analyzes journalistic neutrality and framing in news articles. By
- We [replace](showcases/index.md) the portal page.
- Every headline is reformulated in neutral language (reducing clickbait, overstimulation, persuasion, and framing).
-- Built-in [trend analysis](trends/index.md) for detecting recurring talking points.
+- Built-in [trend analysis](trends/index.md) for detecting recurring talking points and [sentiments](sentiments/index.md) visualization.
- Comparison of major news outlets, e.g., "The New York Times" and the "New York Post" or CNN and Fox News.
- One click restores the original article or the original portal page.
diff --git a/docs/en/links.md b/docs/en/links.md
index 7ef49ae..2cd9013 100644
--- a/docs/en/links.md
+++ b/docs/en/links.md
@@ -5,6 +5,8 @@
- [Source Code](https://github.com/deframer/news-deframer/)
- [Source Code Trend Mining](https://github.com/deframer/news-deframer-mining/)
- [Bug Report](https://github.com/deframer/news-deframer/issues)
+- [MEmoLon – The Multilingual Emotion Lexicon](https://github.com/JULIELab/MEmoLon)
+- [Parquet files for MEmoLon](https://github.com/deframer/memolon-parquet/)
- [License](license.md)
## Contact
diff --git a/docs/en/mobile-app/index.md b/docs/en/mobile-app/index.md
new file mode 100644
index 0000000..3b10e12
--- /dev/null
+++ b/docs/en/mobile-app/index.md
@@ -0,0 +1,3 @@
+# Mobile Application
+
+Coming soon.
diff --git a/docs/en/sentiments/index.md b/docs/en/sentiments/index.md
new file mode 100644
index 0000000..5e3a375
--- /dev/null
+++ b/docs/en/sentiments/index.md
@@ -0,0 +1,12 @@
+# Sentiments
+
+
+
+- **Sentiments**: Displays the emotional scores of the selected articles based on lexical estimates.
+- **Original vs Deframed**: Toggle between original texts from the RSS feed and their deframed counterparts to visualize the emotional impact removed by News Deframer.
+
+## Why Sentiments?
+
+We use a VAD/VAC (Dimensional) and BE5 (Discrete) approach to detect sentiments and emotions in texts, leveraging sentiment scores from [MEmoLon](https://github.com/JULIELab/MEmoLon), an emotion lexicon for 90+ languages. The **VAD** (Valence, Arousal, Dominance) model evaluates overall mood on a 1-9 scale across Valence (polarity/pleasantness), Arousal (activation/excitement), and Dominance (perceived control). The **BE5** model measures the intensity of discrete emotions—Joy, Anger, Sadness, Fear, and Disgust—on a 1-5 scale.
+
+There is fundamental science supporting this methodology: fMRT experiments demonstrate that reading specific words can indeed induce measurable emotional responses in the brain. For more details on this theory, refer to this [PhD thesis](https://edoc.ub.uni-muenchen.de/18933/1/Danner_Sandro_C.pdf).
diff --git a/mkdocs.yml b/mkdocs.yml
index 4251d40..f48bc75 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -46,6 +46,8 @@ plugins:
- News Deframer: index.md
- Showcases: showcases/index.md
- Trends: trends/index.md
+ - Sentiments: sentiments/index.md
+ - Mobile App: mobile-app/index.md
- Status: todo.md
- RSS Proxy: rss-feed.md
- Sponsors: sponsors.md
@@ -59,6 +61,8 @@ plugins:
- News Deframer: index.md
- Showcases: showcases/index.md
- Trends: trends/index.md
+ - Sentiments: sentiments/index.md
+ - Mobile App: mobile-app/index.md
- Status: todo.md
- RSS Proxy: rss-feed.md
- Sponsoren: sponsors.md