SNA Twitter

Conversation, Entertainment, and Information

3.3.1 Introduction: The Rise of the Microblog

• Simplicity as Strategy: Twitter’s success stems from its “brass-tacks” construction: a stream of short messages and an empty box.

• Cultural Impact: Used for political campaigns, fan engagement, and real-time coordination during natural disasters (hurricanes, wildfires) or political turmoil (Iran 2009).

• Growth Milestones: * SXSW 2007: Initial “tech-savvy” buzz.

  • The “Oprah” Effect (2009): Mainstream adoption driven by celebrities like Shaquille O’Neal, Ashton Kutcher, and Oprah Winfrey.

• Ecosystem: Beyond the web interface, third-party clients like TweetDeck and Twhirl allow for specialized views (columns, search queries).

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3.3.2 The Nuts and Bolts

Twitter is a conversational microblog where users post “tweets” limited to 140 characters (originally for SMS compatibility).

Key Terminology

• Followers: People who subscribe to your messages.

• Friends: People whom you follow.

• @replies & @mentions:

  • @reply: A tweet starting with a username (e.g., @redlog). A “marker of addressivity” that keeps conversations coherent in a noisy environment.

  • @mention: Including a name within a tweet but not at the start.

  • Symmetry: While following is often asymmetric (celebrities have fans but don’t follow back), the exchange of @replies creates a symmetric connection, indicating a stronger social tie.

• hashtags: * Community-driven descriptive keywords.

  • Used for events (#chi2010), news (#mumbai), or games (#robotpickuplines).

• Retweeting (RT): * Rebroadcasting someone else’s tweet with attribution.

  • Functions as validation (I like this) and amplification (I want my followers to see this).

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3.3.3 Networks in Twitter: Attention vs. Information

The “Friends/Followers” network is actually two distinct networks overlaying the same people:

1. Attention Network: Follower ties show where attention flows (e.g., from a fan to a celebrity).

2. Information Network: The reverse direction; shows where information flows (from the tweeter to the followers).

Centrality Metrics in Twitter

• Eigenvector Centrality (Importance): Measures influence. You are important if you are followed by other “important” people (similar to Google’s PageRank).

  • Practical Use: Identifying spammers who may have many followers, but whose followers are unimportant/fake.

• Betweenness Centrality (Brokerage): Measures access to non-redundant information.

  • The “Bridge”: An actor who connects two otherwise unconnected clusters. High betweenness actors are “information brokers” who see diverse content first.

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3.3.4 Acquiring Data & Limitations

• NodeXL Options: “From Twitter User’s Network” (Ego-centric) or “From Twitter Search Network” (Topic-centric).

• Rate Limits: Twitter restricts standard accounts to 150 requests per hour. Whitelisting can increase this to 20,000/hour.

• Speed: Data collection is slow (10–30 seconds per user). Mapping a network of 1,000 users can take hours.

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3.3.5 Discovery with NodeXL

3.3.5.1 The Ego Network

• Ego: The focal user. Alters: The user’s friends and followers.

• Strong Ties vs. Weak Ties:

  • Reciprocal Ties: (You follow me, I follow you) usually indicate close friends or colleagues.

  • Closed Triads: If two of your friends know each other, it forms a “closed triad,” suggesting a tight, cohesive community.

• Cluster Detection: Using NodeXL’s “Find Clusters” can automatically separate your Twitter alters into real-world groups (e.g., “Family” vs. “Work Colleagues”).

3.3.5.2 Trending Topics (Information Diffusion)

• Diffusion Patterns:

  • Star Pattern: One user’s tweet is retweeted by many followers (highly influential “seed”).

  • Grid Pattern: Users only mention a topic after seeing it from multiple sources (social influence/redundancy is key).

• Case Study: BlackFriday:

  • Analysis reveals “seeds”—specialized accounts that may have few followers but are highly effective at getting their messages retweeted by larger, more active accounts.

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3.3.6 Practitioner’s Summary

• Strategy is Key: Whether for personal branding or business, you must identify the network structure.

• Starlike networks prioritize the center; Cohesive networks prioritize the group.

• Identify “seeds” (influential promoters) to maximize information spread for free.

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3.3.7 Researcher’s Agenda

• Micro-level: Studying individual features like retweets and @replies.

• Macro-level: Mapping memes, idea spread, and organizational connections across institutional boundaries.

• Challenge: Obtaining and visualizing the “minute details” of human conversation as networks change over time.

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