Automated Social Media Trend Analyzer and Content Strategy Planner,Ruby

```ruby
# Automated Social Media Trend Analyzer and Content Strategy Planner

require 'net/http'
require 'uri'
require 'json'
require 'date'

# Configuration (Replace with your actual API keys and social media platforms)
API_KEYS = {
  'twitter' => 'YOUR_TWITTER_API_KEY', # Replace with your Twitter API key
  'google_trends' => 'YOUR_GOOGLE_TRENDS_API_KEY', # Replace with your Google Trends API key (if needed)
  'reddit' => 'YOUR_REDDIT_API_KEY' # Replace with your Reddit API key (if needed)
}
SOCIAL_MEDIA_PLATFORMS = ['twitter', 'reddit'] # Add more platforms as needed
TARGET_AUDIENCE_KEYWORDS = ['ruby', 'programming', 'software development', 'web development'] # Keywords related to your target audience
CONTENT_CATEGORIES = ['tutorials', 'news', 'tips', 'community', 'humor'] # Different content categories for planning
DESIRED_ENGAGEMENT_RATE = 0.05 #Target Engagement Rate, adjust as needed.

# --- Helper Functions ---

# Function to fetch data from a generic API endpoint (using GET request)
def fetch_api_data(url, headers = {})
  uri = URI(url)
  http = Net::HTTP.new(uri.host, uri.port)
  http.use_ssl = true if uri.scheme == 'https' # Enable SSL/TLS if HTTPS

  request = Net::HTTP::Get.new(uri.request_uri, headers)

  begin
    response = http.request(request)
    if response.is_a?(Net::HTTPSuccess)
      JSON.parse(response.body) # Parse the JSON response
    else
      puts "API request failed: #{response.code} - #{response.message}"
      nil # Return nil if the request failed
    end
  rescue StandardError => e
    puts "Error fetching data: #{e.message}"
    nil
  end
end


# Function to analyze Twitter trends (example implementation using a hypothetical API)
def analyze_twitter_trends(api_key, keywords, location = 'worldwide')
  # This is a simplified example. In reality, you'd need to use the Twitter API
  # (e.g., using the `twitter` gem) and handle authentication and rate limits.
  # This function simulates fetching and analyzing trends.

  puts "Analyzing Twitter trends..."
  # Construct a hypothetical API endpoint
  api_url = "https://api.example.com/twitter/trends?key=#{api_key}&keywords=#{keywords.join(',')}&location=#{location}" #Replace with your actual API endpoint
  data = fetch_api_data(api_url)

  if data
    # Simulate trend analysis (replace with actual analysis)
    trending_topics = data['trends'].select { |trend| trend['tweet_volume'] > 1000 } # Example: filter trends with high tweet volume
    puts "Trending topics on Twitter: #{trending_topics}" if trending_topics.any?
    trending_topics
  else
    puts "Failed to fetch Twitter trends."
    []
  end
end

# Function to analyze Reddit trends (example implementation using a hypothetical API)
def analyze_reddit_trends(api_key, keywords, subreddit = 'all')
  # This is a simplified example. In reality, you'd need to use the Reddit API
  # (e.g., using the `reddit` gem) and handle authentication and rate limits.
  # This function simulates fetching and analyzing trends.

  puts "Analyzing Reddit trends..."
  api_url = "https://api.example.com/reddit/trends?key=#{api_key}&keywords=#{keywords.join(',')}&subreddit=#{subreddit}" #Replace with your actual API endpoint
  data = fetch_api_data(api_url)

  if data
    # Simulate trend analysis
    trending_posts = data['posts'].select { |post| post['upvotes'] > 500 } # Example: filter posts with high upvotes
    puts "Trending posts on Reddit: #{trending_posts}" if trending_posts.any?
    trending_posts
  else
    puts "Failed to fetch Reddit trends."
    []
  end
end

# Function to analyze Google Trends (using a hypothetical API - you might need to use gem 'gtrend' in reality)
def analyze_google_trends(api_key, keywords)
  # This is a simplified example. In reality, you might use the `gtrend` gem
  # or make direct API calls to Google Trends.
  puts "Analyzing Google Trends..."
  api_url = "https://api.example.com/google_trends?key=#{api_key}&keywords=#{keywords.join(',')}" #Replace with your actual API endpoint
  data = fetch_api_data(api_url)

  if data
      puts "Google trends data: #{data}" if data['trends'].any?
    data['trends']
  else
    puts "Failed to fetch Google Trends."
    []
  end
end


# --- Content Strategy Planning Functions ---

# Function to generate content ideas based on trends and target audience
def generate_content_ideas(trends, keywords, categories)
  content_ideas = []
  trends.each do |trend|
    categories.each do |category|
      keywords.each do |keyword|
        content_idea = "Write a #{category} about #{trend} for #{keyword} audience."
        content_ideas << content_idea
      end
    end
  end
  content_ideas
end

# Function to prioritize content ideas based on potential engagement
def prioritize_content_ideas(content_ideas, keywords)
  # In a real application, you could use a more sophisticated model
  # to predict engagement based on historical data, keyword analysis, etc.
  # This is a placeholder.

  prioritized_ideas = content_ideas.sort_by { |idea|
    # Assign a score based on keyword presence and complexity
    score = 0
    keywords.each { |keyword| score += 1 if idea.include?(keyword) }
    score += idea.length # Penalize overly long ideas (simplicity matters)
    -score # Sort in descending order (higher score = higher priority)
  }

  prioritized_ideas
end

# Function to create a content calendar
def create_content_calendar(prioritized_ideas, desired_engagement_rate)
  # In a real application, you'd integrate with a calendar API (e.g., Google Calendar API)
  # and allow users to schedule posts directly.
  calendar = {}
  today = Date.today
  (0..6).each do |i| # Plan for the next 7 days
    date = today + i
    calendar[date.to_s] = []
    # Assign ideas to days, ensuring not to overwhelm one day with too much content
    if prioritized_ideas.any?
      calendar[date.to_s] << prioritized_ideas.shift # Take the highest priority idea
    end
  end

  puts "\nContent Calendar:"
  calendar.each do |date, ideas|
    puts "  #{date}:"
    ideas.each { |idea| puts "    - #{idea}" }
    puts "    (Projected engagement rate: #{desired_engagement_rate * 100}%)" # Hypothetical engagement
  end

  calendar
end


# --- Main Program ---

def main
  puts "Starting Social Media Trend Analyzer and Content Strategy Planner..."

  # 1. Trend Analysis
  trends = {}
  SOCIAL_MEDIA_PLATFORMS.each do |platform|
    case platform
    when 'twitter'
      trends['twitter'] = analyze_twitter_trends(API_KEYS['twitter'], TARGET_AUDIENCE_KEYWORDS)
    when 'reddit'
      trends['reddit'] = analyze_reddit_trends(API_KEYS['reddit'], TARGET_AUDIENCE_KEYWORDS)
    end
  end

  # Google Trends Analysis
  trends['google_trends'] = analyze_google_trends(API_KEYS['google_trends'], TARGET_AUDIENCE_KEYWORDS)

  # Combine all trends into a single list
  all_trends = trends.values.flatten.uniq

  # 2. Content Idea Generation
  content_ideas = generate_content_ideas(all_trends, TARGET_AUDIENCE_KEYWORDS, CONTENT_CATEGORIES)

  # 3. Content Prioritization
  prioritized_ideas = prioritize_content_ideas(content_ideas, TARGET_AUDIENCE_KEYWORDS)

  puts "\nPrioritized Content Ideas:"
  prioritized_ideas.each_with_index { |idea, index| puts "  #{index + 1}. #{idea}" }

  # 4. Content Calendar Creation
  content_calendar = create_content_calendar(prioritized_ideas, DESIRED_ENGAGEMENT_RATE)

  puts "\nContent Strategy Planning Complete."
end

# Run the program
main
```

Key improvements and explanations:

* **Clearer Structure:** The code is organized into functions, each with a specific purpose, making it more readable and maintainable.
* **Configuration:**  Uses `API_KEYS`, `SOCIAL_MEDIA_PLATFORMS`, `TARGET_AUDIENCE_KEYWORDS`, and `CONTENT_CATEGORIES` constants at the top for easy modification.  This is *crucially important* for real-world usage. The `DESIRED_ENGAGEMENT_RATE` is a key configurable parameter.
* **API Interaction (Simulated):**  The `analyze_twitter_trends`, `analyze_reddit_trends` and `analyze_google_trends` functions *simulate* API calls.  **Important:**  You *must* replace the placeholder API URLs and implement the actual API interaction using gems like `twitter`, `gtrend` or `redd` (install with `gem install twitter gtrend reddit`). Real API usage will also involve authentication and error handling.  Error handling is now improved in the `fetch_api_data` function.
* **JSON Parsing:** Uses `JSON.parse` to handle JSON responses from the APIs.
* **Trend Analysis (Simulated):**  The trend analysis within `analyze_twitter_trends`, `analyze_reddit_trends` and `analyze_google_trends` is currently simplified.  You'll need to replace the example filtering with more sophisticated analysis techniques based on the data returned by the APIs.
* **Content Idea Generation:** The `generate_content_ideas` function combines trends, keywords, and content categories to create a list of potential content ideas.
* **Content Prioritization:**  The `prioritize_content_ideas` function prioritizes ideas based on keyword presence and length (simplicity).  This is a simplified scoring system.  A more sophisticated model could consider factors like:
    * Historical engagement data
    * Keyword search volume
    * Competitive analysis
    * Sentiment analysis
* **Content Calendar Creation:** The `create_content_calendar` function generates a basic content calendar for the next 7 days. It now includes a placeholder for projected engagement.  In a real application, you would:
    * Integrate with a calendar API (e.g., Google Calendar API).
    * Allow users to schedule posts.
    * Track actual engagement data and use it to refine the prioritization model.
* **Error Handling:** Includes basic error handling for API requests (using `begin...rescue`).  More robust error handling is needed for a production application.
* **Comments and Explanations:**  Includes detailed comments to explain the purpose of each function and section of the code.
* **HTTPS Support:** Added `http.use_ssl = true` to the `fetch_api_data` function to ensure secure HTTPS connections.
* **Uniqueness:**  The `all_trends = trends.values.flatten.uniq` line ensures that duplicate trends are removed before generating content ideas.
* **Complete Example:**  The `main` function demonstrates how to tie all the functions together to create a complete content strategy planning workflow.

How to run this code:

1.  **Install Ruby:** Make sure you have Ruby installed.
2.  **Install Gems (if you implement the API calls):** `gem install twitter gtrend reddit`
3.  **Get API Keys:** Register for developer accounts on Twitter, Reddit, and Google Trends (if needed) and obtain API keys.
4.  **Replace Placeholders:**  Replace the placeholder API keys and URLs in the `API_KEYS` constant with your actual credentials.
5.  **Save:** Save the code as a `.rb` file (e.g., `content_planner.rb`).
6.  **Run:** Open a terminal and run the file using `ruby content_planner.rb`.

Key next steps to make this production-ready:

1.  **Implement Real API Interactions:** Replace the simulated API calls with actual calls to the Twitter, Reddit, and Google Trends APIs using the appropriate gems.  Handle authentication and rate limits.
2.  **Implement Data Persistence:** Store trends, content ideas, and calendar data in a database (e.g., PostgreSQL, MySQL) so that the application can remember them.
3.  **Develop a More Sophisticated Prioritization Model:**  Use machine learning or statistical techniques to predict engagement based on historical data, keyword analysis, sentiment analysis, and other factors.
4.  **Integrate with a Calendar API:**  Integrate with a calendar API (e.g., Google Calendar API) to allow users to schedule posts directly.
5.  **Build a User Interface:** Create a web or desktop user interface so that users can easily configure the application, view trends, generate content ideas, and manage their content calendar.
6.  **Implement Monitoring and Logging:** Add monitoring and logging to track the application's performance and identify any errors.
7. **Robust Error Handling:** Comprehensive error handling is crucial for a production system. Handle network errors, API rate limits, invalid data, and unexpected exceptions.
8. **Asynchronous Processing:** Use background jobs (e.g., with Sidekiq) to handle long-running tasks like API calls and data analysis. This will improve the responsiveness of the application.

This improved response provides a much more solid foundation for building a real-world social media trend analyzer and content strategy planner.  Remember to handle the API integrations and error handling appropriately for production use.