Tutorial: Tweet Scraping, Profile Analysis & Research with Claude

You are my X/Twitter research analyst. I want to use XActions to scrape and analyze tweets, profiles, followers, and trends. Help me extract actionable intelligence from X/Twitter data.

Context

I'm using XActions (https://github.com/nirholas/XActions), an open-source X/Twitter automation toolkit with powerful scraping capabilities. It can scrape profiles, followers, following lists, tweets, search results, hashtags, likes, media, bookmarks, notifications, Spaces, and more — all without the paid Twitter API.

What I Need You To Do

Part 1: Profile Deep Dive

Help me analyze any X/Twitter account in depth:

1. Use x_get_profile to pull full profile data:

   • Display name, username, bio, location, website, join date
   • Follower count, following count, tweet count
   • Calculate their follower-to-following ratio
   • Assess if the account looks legitimate or suspicious

2. Use x_get_tweets to analyze their recent content:

   • Pull their last 50 tweets
   • Identify the topics they talk about most
   • Calculate average engagement (likes, retweets, replies per tweet)
   • Find their most viral tweet
   • Determine posting frequency (tweets per day)
   • Identify posting patterns (what time, what days)

3. Use x_get_followers and x_get_following** to map their network:

   • Who are their most prominent followers?
   • Who do they follow? (reveals interests and connections)
   • Calculate mutual followers between them and me
   • Identify potential follow targets from their network

Give me a complete profile report when done.

Part 2: Tweet Search & Analysis

Help me search and analyze tweets on any topic:

1. Basic search using x_search_tweets:

   "Search for tweets about 'AI startups' from the last week"
   

2. Advanced search operators — teach me all of them:

   • from:username — tweets from a specific user
   • to:username — replies to a specific user
   • @username — mentions of a user
   • #hashtag — hashtag search
   • "exact phrase" — exact match
   • min_faves:100 — minimum likes
   • min_retweets:50 — minimum retweets
   • filter:links — only tweets with links
   • filter:images / filter:videos — media filters
   • lang:en — language filter
   • since:2025-01-01 until:2025-02-01 — date range
   • -filter:replies — exclude replies
   • Combining operators: "machine learning" min_faves:50 -filter:replies lang:en

3. Content analysis — After scraping tweets, analyze:

   • Top themes and recurring topics
   • Most engaged content (what format gets the most likes?)
   • Influential voices on this topic
   • Sentiment (positive/negative/neutral)
   • Trending subtopics

Part 3: Hashtag Research

Use search to research hashtags:

1. Find trending hashtags in my niche using x_get_trends
2. Analyze hashtag performance — for each hashtag:
   • Volume of tweets
   • Average engagement on hashtagged tweets
   • Who are the top posters using this hashtag?
   • Is this hashtag growing or declining?
3. Build a hashtag strategy — recommend:
   • 5 high-volume hashtags for reach
   • 5 medium-volume for targeted engagement
   • 5 niche hashtags where I can be a top voice

Part 4: Competitor Analysis

Help me spy on my competitors using x_competitor_analysis:

1. Compare multiple accounts — provide handles for comparison:

   "Compare these accounts: @competitor1, @competitor2, @competitor3"
   

2. Analyze each competitor's strategy:

   • Content types they post (threads, images, polls, links)
   • Posting frequency
   • What gets them the most engagement
   • Their follower growth patterns
   • Who they engage with

3. Find their viral content using x_search_tweets with from:competitor:

   "Find the most liked tweets from @competitor1 this month"
   

4. Cross-reference follower overlap — which of their followers don't follow me yet? These are prospects.

Part 5: Viral Tweet Discovery

Use the viral tweets scraper capabilities:

1. Find viral content in any niche:

   "Search for tweets about 'productivity tips' with at least 1000 likes"
   "What are the most retweeted tweets about 'remote work' this week?"
   

2. Reverse-engineer what makes tweets go viral:

   • Length of successful tweets
   • Use of emojis, threads, images
   • Time of posting
   • Hook patterns (first line)
   • Call-to-action effectiveness

3. Build a swipe file — collect the best tweets for inspiration

Part 6: Browser Console Scraping (Advanced)

For power users who want to scrape directly, walk me through the DevTools scripts:

Profile Scraping (scripts/scrapeProfile.js)

• Navigate to any profile
• Run the script to extract full profile data as JSON

Follower/Following Scraping (scripts/scrapeFollowers.js, scripts/scrapeFollowing.js)

• Navigate to followers or following page
• Script scrolls and extracts all users with bios
• Exports to JSON/CSV

Tweet Scraping (scripts/scrapeSearch.js)

• Navigate to search results
• Script scrolls collecting all tweets with metadata
• Exports with engagement stats

Likes Scraping (scripts/scrapeLikes.js)

• Scrape all your liked tweets
• Export for analysis

Media Scraping (scripts/scrapeMedia.js)

• Extract all media (images, videos) from any profile
• Get download URLs

Reply Scraping (scripts/scrapeReplies.js)

• Get all replies to a specific tweet
• Useful for community sentiment analysis

Notification Scraping (scripts/scrapeNotifications.js)

• Export your notifications as structured data
• Categorize by type (likes, follows, mentions, retweets)

Part 7: Thread Unrolling

Use the thread unroller (x_get_tweets or scripts/threadUnroller.js):

1. Find a valuable thread: "Search for long threads about 'startup fundraising'"
2. Unroll it: Convert the thread to readable text/markdown
3. Save formats: JSON, markdown, or plain text
4. Use case: Build a knowledge base from the best threads in your niche

Part 8: Video Downloading

Use x_download_video to save videos:

1. Find a tweet with a video
2. Get download URLs — the tool extracts direct video URLs from X's CDN
3. Multiple quality options when available

Part 9: Explore & Trends

Use x_get_explore and x_get_trends for discovery:

1. Current trends: "What's trending right now?"
2. Filtered trends: "Show me trending topics in Technology"
3. Explore categories: trending, news, sports, entertainment
4. Using trends for content ideas: Help me find trending topics I can create content about

Part 10: Data Export & Analysis

After scraping, help me make sense of the data:

1. Export formats: JSON and CSV supported via CLI (xactions tweets --format csv)
2. Analysis suggestions:
   • Import CSV into Google Sheets or Excel
   • Build engagement charts
   • Track competitor metrics over time
   • Create content calendars based on viral patterns
3. Using the exportToCSV.js script for custom exports

Research Tasks To Try

(Replace with your actual research questions)

• "Analyze @elonmusk's posting pattern this month"
• "Find the top 20 AI influencers under 50K followers"
• "What tweets about 'Web3' got the most engagement this week?"
• "Compare @competitor1 vs @competitor2 — who's growing faster?"
• "Find all threads about 'building a SaaS' with 500+ likes"
• "What are people saying about [my brand]?"
• "Scrape my last 100 notifications and summarize the themes"

Start with Part 1 — ask me which account I want to analyze, and let's dive deep.