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Visits: Mapping the Places you Have Visited

Posted by on Sep 1, 2014 in Blog, Data Visualization | Comments Off on Visits: Mapping the Places you Have Visited

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Visits [v.isits.in] automatically visualizes personal location histories, trips and travels by aggregating geotagged one’s Flickr collection with a Google Maps history. developed by Alice Thudt, Dominkus Baur and prof. Sheelagh Carpendale, the map runs locally in the browser, so no sensitive data is uploaded to external servers.

The timeline visualization goes beyond the classical pin representation, which tend to overlap and are relatively hard to read. Instead, the data is shown as ‘map-timelines’, a combination of maps with a timeline that convey location histories as sequences of maps: the bigger the map, the longer the stay. This way, the temporal sequence is clear, as the trip starts with the map on the left and continues towards the right.

A place slider allows the adjusting of the map granularity, reaching from street-level to country-level.

Read the academic research here [PDF]

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Culturegraphy: the Cultural Influences and References between Movies

Posted by on Aug 22, 2014 in Blog, Data Visualization | Comments Off on Culturegraphy: the Cultural Influences and References between Movies

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Culturegraphy [culturegraphy.com], developed by “Information Model Maker” Kim Albrecht reveals represent complex relationships of over 100 years of movie references.

Movies are shown as unique nodes, while their influences are depicted as directed edges. The color gradients from blue to red that originate in the 1980s denote the era of postmodern cinema, the era in which movies tend to adapt and combine references from other movies.

Although the visualizations look rather minimalistic at first sight, their interactive features are quite sophisticated and the resulting insights are naturally interesting. Therefore, do not miss out the explanatory movie below.

Via @albertocairo .

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Beatquake: the Music Listening Activity across Facebook over 90 days

Posted by on May 28, 2014 in Blog, Data Visualization | Comments Off on Beatquake: the Music Listening Activity across Facebook over 90 days

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Mapping Music on Facebook [facebookstories.com] by Stamen Design for Facebook shows the dynamic characteristics of the typical listening activity across Facebook.

Inspired by the dynamic movement of a graphic equalizer, Beatquake maps the popularity of the top three most popular songs in the U.S., each day over the course of 90 days, by way of vertically moving particles.

Colored layers, each representing one song, rise and fall over geographic locations to correspond with the number of plays in that area. The texture of the map is driven by BPMs (beats per minute), and thus changes as one song overtakes another in popularity.

 

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Will “Daily Deals” Save Newspapers?

Posted by on Jan 11, 2014 in Blog, Media and Markets | Comments Off on Will “Daily Deals” Save Newspapers?

dailydeals?Groupon is Hastening the Demise of the Newspaper Industry,? wrote a trade publication in April 2011.?? However,?? some newspapers are betting that ?daily deal? offerings could reinvigorate the industry.?? Newspapers are turning to startups such as?? Shoutback and Nimble Commerce?? and others offering consulting and white-label systems to power deal mechanisms. And newspapers have other things many other Groupon clones don?t ? large local audiences that are still used to turning to newspapers for coupons,? and a sales force with established local relationships.

Reportedly,?? The Boston Globe is offering its own? Boston Deals promo after? trying a partnership? with BuyWithMe last year (and SCVNGR, also last year)? as it? moves to separate? its online content from a potentially more lucrative e-commerce business.??? Boston Phoenix? offers? deals,? Star Tribune? in the Twin Cities offers STeals.

The struggle newspapers have had in recent years to make money from their content is obvious to all.?? Paywalls,???? apps, etc., have all been attempted.

But newspapers have failed to leverage the single most important advantage they have over the emerging media types:???? local audiences and local sales relationships.?? An intelligent ?Daily Deals? offering could be the key.???? The Globe, Phoenix and Star Tribune have each come out with their own versions of this play. Or they could aggregate local deals from Groupon and its numerous clones, Yipit-style.?? ((These last observations are from MIT?s Advertising Lab?s excellent blog.)

Has any newspaper actually tried to recapture the classifieds business from Craiglist????? Newspapers ought to be able to offer online classifieds with more power and usability than the Craigslist version, with a little planning and proper research.

In the past year I?ve spent a lot of time talking to local businesses in southern California and trying to understand their experience with the ?Groupon? concept, which many have tried and abandoned.?? The reason??? Yes,?? ?daily deal? promos bring business in the door,?? but sporadically and often at a loss to the retailer.?? Local businesses have not figured out how to capture the Daily Deals crowd and turn them into reliable repeat customers, and that is something that newspapers will need to consider if they plan on competing in this deal space.?? Newspapers could step into this void and help local businesses profit from Daily Deals, thereby strengthening their own brands and relationships.

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YouTube Trends Map: Explore the Most Popular Videos by Location

Posted by on May 9, 2013 in Blog, Data Visualization | Comments Off on YouTube Trends Map: Explore the Most Popular Videos by Location

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The YouTube Trends Map [youtube.com] is a visualization of the most shared and viewed videos in various regions across the United States over the last 12 to 24 hours. It accompanies the more analytical Trends Dashboard to provide a full overview of the the rising videos and trends on YouTube in terms of actual views or shares, filtered by geographical location, gender or age of the viewers.

The demographic information of viewers is solely based on the information reported by registered, logged-in users in their YouTube account profiles. Next to the geographical map, the Trends Map also include a series of horizontal bar graphs, each representing a graphical summary of the top videos for a different demographic. Within each bar, a video is represented by a colorful segment, the colors are drawn from the video’s thumbnail. The width of a video’s segment reflects the number of regions on the map where the video is #1.

See also:
. YouTube View Tracking Data Visualization
. YouTube Swarm Related Videos

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