1 Web Search and Web Search Overlap: What the Deal? Amanda Spink Queensland University of Technology.

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Presentation transcript:

1 Web Search and Web Search Overlap: What the Deal? Amanda Spink Queensland University of Technology

2 My Talk Today Web search challenges How do people search the Web? What do we know about Web search overlap? Web search trends and challenges

3 Electronic Information Challenge Electronic information management is a challenging area for organisations and people How to collect, organise, maintain and provide access to electronic information? Poor information systems billions $ in lost productivity Still learning about people’s information behaviours

4 Web Search Challenge Many people Web search daily Web search engine usage is projected to soon outstrip as the primary Internet application Web search is now a major social issue – people are expected to search effectively

5 Web Search Engines Web search engines are generally commercial products with brand identities, e.g., Google Desk-top wars – MSN versus Google Studies show that people are satisfied with their searching, but know little about Web search engines

6 Web Search Engine Overlap For any Web query – what is the overlap on the first page of results for Yahoo, Google, MSN and Ask Jeeves? 3% - very low overlap for the same query across different Web search engines Implications – different Web search engines index different Websites

7 Web Search Engine Overlap No Web search engine covers the complete Web Web search engines have different crawling policies – how frequently and deep into a Website and what Websites. Single versus meta-search engines Meta-search engines allow you to search multiple Web search engines simultaneously, e.g., Dogpile, Metacrawler, Hotbot, Mamma, etc.

8 How People Search the Web Track Web search trends Identify characteristics of Web searching - search length, query length, and use of advanced features. Examine the distribution of query topics, terms, queries, sources, and languages used on Web search engines. Implications for society, business, Web services, interfaces and systems design.

9 Web Query Datasets Web query transaction logs collected in 1997,1999, 2001, 2003, 2004, 2005 & Combined dataset of 25 million+ Web searches

10 Web Search Engines Excite.com Ask.com AlltheWeb.com AltaVista.com Vivisimo.com Dogpile.com AOL No Google, Yahoo or MSN data

11 Queries Per Web Search Sessions are SHORT in queries, but getting longer

12 Terms Per Web Query SHORT QUERIES: But increasing towards 3 terms per query

13 Web Search Duration (Minutes) < 1 minute 56.6% 1 minute to < 5 minutes 15.5% 5 to < 10 minutes 6.8% 10 minutes + 20%

14 Use of Advanced Web Search Features Many uses of advanced search features are used incorrectly Poor spelling

15 Results Pages Viewed Most users view VERY FEW pages beyond the first or first two pages. 14% of users view Web pages for less than 30 seconds

16 Search Term Distribution

17 Top 10 Web Search Terms

18 Top 10 Co-Occurring Terms

19 Web Query Topics

20 Web Query Topics Commerce, Travel, Employment or Economy21% 2. Indiscernible or Non-English19% 3. People, Places or Things15% 4. Computers or Internet13% 5. Social, Culture, Ethnic or Religion9% 6. Health or Sciences6% 7. Education or Humanities5% 8. Sex or Pornography4% 9. Performing or Fine Arts3% 10. Government3% 11. Entertainment or Recreation2%

21 Web Query Topics Commerce, Travel, Employment or Economy30.4% 2. Indiscernible or Non-English13.2% 3. People, Places or Things16% 4. Computers or Internet13% 5. Social, Culture, Ethnic or Religion9% 6. Health or Sciences6% 7. Education or Humanities5% 8. Sex or Pornography4% 9. Performing or Fine Arts3% 10. Government3% 11. Entertainment or Recreation2%

22 Typical Web Searches Short Web searches – getting longer Shift from entertainment queries to e- commerce/people queries Sex / pornography queries > 4% Increasing number of non-English queries More query reformulation Less results and Web page viewing

23 Implications Finding electronic information is often difficult and often time-consuming - effects productivity Proliferation of Web search tools Most people are not trained to search Incremental change – no silver bullet!

24 New Web Technologies Visualization interfaces Clustering techniques Larger query boxes More systems assistance for users Multitasking support Longitudinal searching

25 Systems Design Challenges Support information behaviors not just behaviors of technologists Design to support/help humans bridge their training gap Help humans express and resolve complex information problems Measure how systems impact on human information behaviors

26 User Challenges No technology silver bullet Need to improve information behaviors and search expertise People learn and think more about their information behaviors People learning information tools and training

27 Conclusions Web search is changing - incrementally Some user characteristics are relatively stable and some changing incrementally Better usability testing Web search engine systems and interfaces? Continue research to identify trends in Web search with Dogpile and AOL data.

28 THANK YOU