Actve Sports Fig 3. Counterexample photos for particular tourist types significant coefficients in the regression model are regarded as affirmative exam- ples for a particular tourist type. Conversely, photos with negative, significant coefficients are counterexamples. Following this approach, we obtain the map- pings of photos to tourist types as given in Figure 2 and Figure 3. We indicate the significance levels with asterisks: ***(a=0.001 )and **(a=0.01) Regarding the affirmative examples (cf. Figure 2), we obtain impressive re sults for characterizing the following tourist types: Anthropologist(photo 0 a group of indigenous musicians), Archaeologist (photo 34- the remnants of an ancient Greek temple), Sun Lover(photo 25-the beach), High Class(photo 24 the entrance hall of a stylish hotel: photo 31-a posh bar), Organized Mass Tourist (photo 14- group of bus tourists), Active Sports(photo 39-cyclists) Action Seeker(photo 29-a party), and Thrill Seeker(photo 46-whitewater rafting: photo 52- sky diving). However, we also recognized the rather unex- pected phenomenon that photo 38, showing the Burj al-Arab hotel in Dubai, is representative for six tourist types. This particular photo was selected by 163 participants. So, we assume that a fairly large number of participants regarded photo 38 as their emblematic vacation dream rather than their vacation prac- ce. For the counterexamples(cf. Figure 3), we refer to photo 54 depicting a street musician. The selection of this photo significantly excludes the member- ship to the archaeologist. Photo 13, showing a tranquil scenery with boat, is a perfect example against the typical Active Sports tourist. Finally, we want to mention that only for a small number of tourist types we were unable to identify mportant photos, viz. Seeker, Explorer and Drifter. 5 Photo- Based profiling We have designed and implemented a Web-based tourist type profiling tool as shown in Figure 4 using the statistical model established by the logistic re- gression. Eight sets of photographs are located in the top row and users may switch from one set to the next by clicking the respective hyperlink. Users may drag photographs they identify with into the lower-left area. If they change their mind, photos can be dragged to the area bordering right, the "Wastebin", to ex- clude them from their selection. Note, however, photos moved to the"Wastebin Giveitagoathttp://ispaces.ec3.at/tourismpRofiler/index.html52 H. Berger et al. Fig. 3. Counterexample photos for particular tourist types significant coefficients in the regression model are regarded as affirmative exam￾ples for a particular tourist type. Conversely, photos with negative, significant coefficients are counterexamples. Following this approach, we obtain the map￾pings of photos to tourist types as given in Figure 2 and Figure 3. We indicate the significance levels with asterisks: *** (α = 0.001) and ** (α = 0.01). Regarding the affirmative examples (cf. Figure 2), we obtain impressive re￾sults for characterizing the following tourist types: Anthropologist (photo 02 - a group of indigenous musicians), Archaeologist (photo 34 - the remnants of an ancient Greek temple), Sun Lover (photo 25 - the beach), High Class (photo 24 - the entrance hall of a stylish hotel; photo 31 - a posh bar), Organized Mass Tourist (photo 14 - group of bus tourists), Active Sports (photo 39 - cyclists), Action Seeker (photo 29 - a party), and Thrill Seeker (photo 46 - whitewater rafting; photo 52 - sky diving). However, we also recognized the rather unex￾pected phenomenon that photo 38, showing the Burj al-Arab hotel in Dubai, is representative for six tourist types. This particular photo was selected by 163 participants. So, we assume that a fairly large number of participants regarded photo 38 as their emblematic vacation dream rather than their vacation prac￾tice. For the counterexamples (cf. Figure 3), we refer to photo 54 depicting a street musician. The selection of this photo significantly excludes the member￾ship to the Archaeologist. Photo 13, showing a tranquil scenery with boat, is a perfect example against the typical Active Sports tourist. Finally, we want to mention that only for a small number of tourist types we were unable to identify important photos, viz. Seeker, Explorer and Drifter. 5 Photo-Based Profiling We have designed and implemented a Web-based tourist type profiling tool1 as shown in Figure 4 using the statistical model established by the logistic re￾gression. Eight sets of photographs are located in the top row and users may switch from one set to the next by clicking the respective hyperlink. Users may drag photographs they identify with into the lower-left area. If they change their mind, photos can be dragged to the area bordering right, the “Wastebin”, to ex￾clude them from their selection. Note, however, photos moved to the “Wastebin” 1 Give it a go at http://ispaces.ec3.at/TourismProfiler/index.html