1. How has sentiment towards CCSS and NGSS changed over time?

• This explores whether public opinion on educational standards has become more positive or negative over time.

2. How do different emotions (joy, anger, disgust, etc.) compare between CCSS and NGSS tweets?

• This examines whether different emotions are more prevalent in discussions about CCSS vs. NGSS.

📌 Connection to Previous Work (Unit 2 Case Study)

• This analysis builds on last week’s Unit 2 case study, where we examined sentiment around CCSS and NGSS.

• We are now focusing on:
  ✅ How sentiment has evolved over time.
  ✅ How emotions vary between CCSS and NGSS discussions.

📌 Data Source

• The dataset used is ccss-tweets.csv from Unit 2 Analysis project.

• It includes tweets from discussions about CCSS (Common Core) and NGSS (Next Generation Science Standards).

• 1️⃣ Data Collection

  • Dataset: ccss-tweets.csv (From Unit 2 Case Study)

  2️⃣ Data Preprocessing

  • Text cleaning: Removed stopwords, URLs, punctuation, and unnecessary characters.

  • Tokenization: Split tweets into words for sentiment/emotion scoring.

  • Sentiment scoring: Used the Bing, AFINN, and NRC lexicons to classify words as positive/negative.

3️⃣ Sentiment & Engagement Analysis

Question 1: How has sentiment changed over time?

• ✅ Converted tweet timestamps into monthly data.
  ✅ Grouped tweets by sentiment (positive/negative) and month to analyze trends.
  ✅ Visualized sentiment change over time using line charts for CCSS & NGSS.

3️⃣ Sentiment & Engagement Analysis (Continued)

Question 2: How do different emotions (joy, anger, disgust, etc.) compare between CCSS and NGSS tweets?

✅ Extracted emotion categories (joy, anger, anticipation, trust, etc.) from the NRC lexicon.
✅ Grouped by educational standard (CCSS vs. NGSS) to count occurrences of each emotion.
✅ Normalized emotion counts to allow fair comparisons.
✅ Visualized results using bar charts to show the distribution of emotions across CCSS & NGSS

4️⃣ Visualization & Interpretation

📊 Line Charts: Monthly sentiment trends for CCSS & NGSS.
📊 Bar Charts: Comparison of different emotions in CCSS vs. NGSS tweets.

• NGSS has an upward trend with fluctuations but remains positive.

• CCSS sentiment remains relatively stable with minor fluctuations around neutral or slightly negative values.

• There is no dramatic shift in sentiment for either standard, but NGSS maintains a stronger positive sentiment over time.

• CCSS tweets have a stronger presence of negative emotions (anger, fear, and disgust), indicating that it may receive more criticism.

• NGSS tweets have relatively more joy and positive anticipation, suggesting a slightly better public perception.

• Trust remains the dominant emotion in both, but CCSS has significantly higher trust-related tweets.

• CCSS sentiment is generally more negative, while NGSS sentiment is more positive over time.
• Trust is the most common emotion in both, but CCSS discussions contain more anger, fear, and disgust compared to NGSS.
• NGSS tweets show more joy and anticipation, indicating a more optimistic perception.

• 🔹 Implications: Sentiment trends can guide policymakers and educators in improving public communication about CCSS and NGSS.
• ⚠ Limitations: Twitter users may not represent the general public, and sentiment analysis may misinterpret sarcasm or nuanced discussions.
• 🔍 Future Analysis: Expanding the study to other social media platforms and applying machine learning could provide deeper insights.