A Comparison of Microblog Search and Web Search.

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Presentation transcript:

A Comparison of Microblog Search and Web Search

WSDM Microblog Papers TwitterRank: Finding topic-sensitive influential Twitterers [Weng, Lim, Jiang, He] Everyone's an influencer: Quantifying influence on Twitter [Bakshy, Hofman, Mason, Watts] Learning concept importance using a weighted dependence model [Bendersky, Metzler, Croft] Early online identification of attention gathering items in social media [Mathioudakis, Koudas, Marbach] Identifying topical authorities in microblogs [Pal, Counts] Transient crowd discovery on the real-time social Web [Yeshwanth, Caverlee] We feel fine and searching the emotional Web [Kamvar, Harris] Topical semantics of Twitter links [Welch, Schonfeld, He, Cho]

But How is Microblog Search Used?

Past Surprises About Web Search Early log analysis ( [Jansen et al. 2000; Broder 1998] ) Queries are not 7 or 8 words long Advanced operators not used or “misused” Nobody used relevance feedback Lots of people search for sex Navigation behavior common  Prior experience was with library search

Microblog Search Surprises?

Ordered by time Ordered by time Ordered by relevance 8 new tweets

Methodology Survey of 54 Microsoft Twitter users Query log analysis – Twitter queries issued to Sample of 33k users over 2 weeks 126k queries – Web queries issued to Bing, Google, and Yahoo! For the users who issued Twitter queries 2.5 million queries Comparison of search results

Methodology Survey of 54 Microsoft Twitter users Query log analysis – Twitter queries issued to Sample of 33k users 126k queries over 2 weeks – Web queries issued to Bing, Google, and Yahoo! For the users who issued Twitter queries 2.5 million queries Comparison of search results Queries issued Temporal patterns Cross-corpus behavior

Top Web Queries Issued WebTwitter twitternew moon youtube#youknowyouruglyif facebookjustin bieber googleadam lambert myspace#theresway2many youtube.comtaylor swift yahoolady gaga ebaymodern warfare 2 craigslistthanksgiving myspace.com#wecoolandallbut Top Web queries navigational – Learn more today after lunch Biased towards social networking sites because of our user sample Twitter queries cannot be navigational

Top Twitter Queries Issued WebTwitter twitternew moon youtube#youknowyouruglyif facebookjustin bieber googleadam lambert myspace#theresway2many youtube.comtaylor swift yahoolady gaga ebaymodern warfare 2 craigslistthanksgiving myspace.com#wecoolandallbut People-focused Temporal aspects Specialized syntax

People and Time in Twitter Queries Lots of celebrity names – lady gaga Celebrities unlikely to just be part of a query – lady gaga meat dress Many references to individual user accounts Hashtags common – Memes, trending topics WebTwitter Is a celebrity name 3.1%15.2% Mentions a celebrity 14.9%6.5% 0.1%3.4% Is a username 0.0%2.4% Contains # 0.1%21.3% Is a hashtag without # 3.0%4.4%

Twitter and # Specialized syntax very common for and # reduce ambiguity like advanced query operators Important differences: – Part of content creation – Hashtag queries often issued via a click WebTwitter Is a celebrity name 3.1%15.2% Mentions a celebrity 14.9%6.5% 0.1%3.4% Is a username 0.0%2.4% Contains # 0.1%21.3% Is a hashtag without # 3.0%4.4%

Twitter Query Popularity Hashtag queries particularly popular – Most popular queries: Hashtag 51% of the time – Least popular queries: Hashtag 7% of the time Celebrity queries particularly popular – Most popular queries: Celebrity 25% of the time – Least popular queries: Celebrity 4% of the time Twitter queries less diverse than Web queries – Only 1 in 4 unique (v. 2 in 4 unique)

WebTwitter Number of queries in session Number of unique queries in session Seconds between queries in session Temporal Patterns on Twitter Individuals repeat the same query on Twitter – 35% of Web queries are repeat – 56% of Twitter queries are repeat But sessions are shorter  Twitter queries used for monitoring

Cross-Corpus Behavior Some users issued same query to Twitter & Web Overlapping queries highly informational Web used to explore – Overlapping query is 8 times more likely to appear in another query Twitter used to monitor hong kong weather in hong kong hong kong restaurants hong kong … … sheraton hong kong

How Microblog and Web Search Differ Ordered by time Ordered by time Ordered by relevance 8 new tweets Time important People important Specialized syntax Queries common Repeated a lot Change very little Often navigational Time and people less important No syntax use Queries longer Queries develop

Questions?