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A Case Study on How Popularity Works on Flickr: Exploring the Patterns and Trends of Image Popularit



Matthew Almon Roth:As Goldendrake2 above mentions, the new "popular' feature only displays a tiny fraction of our stream, for interestingness, views, favorites and comments. In the "old" profile "200 bits" were listed for each category, and you could/can even go beyond by editing the page number in the URL. Soooo regrettable this feature has been reduced to a symbolic presence of a mere 25 images. This feature is not just for proudly showing *others* how things stand with the popularity of our images, we ourselves might like to check up way back to compare. I am conjecturing that the feature garnered too few clicks by "Flickr's Click Tracker" to stand the test ?ETA: those pages can still be accessed through Stats, but then of course only for the PRO account holders. See this staff response:www.flickr.com/help/forum/en-us/72157681711158094/page2/#...Posted 69 months ago.( permalink) MabelAmber***Pluto5339***MysteryGuest edited this topic 69 months ago.


In this paper, we analyse social media data collected from three platforms that are mostly used for research purposes, namely Instagram, Twitter and Flickr, and assess how well these data, separately and combined, can be used to estimate visitation patterns in national parks. In particular, we systematically investigate whether or not social media data can identify 1) the popularity of the parks (ranking), and 2) the monthly visitation rates of the parks. Furthermore, we 3) assess whether there are platform-specific differences in the correlations between social media data and official visitor statistics. In addition to statistical comparisons, we 4) identify different factors that could explain where social media data has a strong relationship with official visitor statistics, and where it does not. We do this by conducting semi-structured group-interviews with stakeholders, capturing their interpretations of these results. We conduct our analyses in 56 national parks located in two different countries: 21 in South Africa and 35 in Finland (Fig. 1a,b). The chosen countries form a good sample for the study as they differ in culture, economy, biodiversity, climate, and tourism profiles. In addition, South African and Finnish park authorities both collect up-to-date official visitor statistics that are needed to address the study questions.




A Case Study on How Popularity Works on Flickr




Our study combined data from two very distinct countries, with different profiles of national park visitors. In South Africa, the number of foreign visitors in national parks is considerably higher than in Finland, the cultural background is much more varied and people use the parks differently. For example, in Finland most national parks are visited for outdoor activities such as hiking or skiing, while in South Africa game driving and observing large-bodied charismatic species are the most popular attractions54. Regardless of the country-wise differences, our results are robustly suggesting that social media data has the potential to inform about visitor patterns in national parks. This is encouraging also for other areas of the world, where social media platforms are being used, but no official statistics are similarly available as in our example countries. Social media data is also available across country borders and could inform global conservation55. For example, it could contribute to estimating the global scale visitation patterns in protected areas in a similar manner as was done by Balmford et al.2 using visitor statistics. Moreover, social media data could be used to assess the intensity of human activities at a global scale, in order to inform spatial conservation prioritization of protected areas under pressure3. While we found that more than half of the national parks worldwide have social media activity, country-wise differences in social media platform popularity may be a limitation to this result. Hence, including platforms such as QQ or Sina Weibo (popular among Chinese speaking population) or VKontakte (popular in the Russian speaking world), may help improve the coverage of underrepresented countries.


Social media data used in this study includes posts from year 2014 that were collected from Instagram (www.instagram.com/developer), Flickr (www.flickr.com/api) and Twitter (dev.twitter.com/). Overall, Instagram was the most popular social media platform among the three (see Table 1), having the highest number of posts (46%), unique social media users (76%) and social media user days (71%). There are some country and platform specific peculiarities such as the fact that in Finland Twitter had the highest number of posts (52% of all posts). However, the number of unique Twitter users is much lower (16%) compared to Instagram (82%). Flickr is overall the least popular platform with all represented measures.


In this case study, we compare the normalized number of Hurricane Sandy related Flickr photos taken to a direct measure of the environment during the development of Hurricane Sandy: the atmospheric pressure in the US state New Jersey between 20 October 2012 and 20 November 2012 (Figure 1B). Atmospheric pressure data are compiled from average measurements from 62 stations in New Jersey forming part of the Automated Surface Observing System (ASOS) and are analyzed at an hourly granularity.


We suggest that Flickr can be considered as a system of large scale real-time sensors documenting collective human attention. The analysis of other examples of catastrophic events, beyond this case study of Hurricane Sandy, is however needed to evaluate whether an appropriate leverage of such a system could be of interest to policy makers and others charged with emergency crisis management.


Society's increasing interactions with technology are creating extensive ``digital traces'' of our collective human behavior. These new data sources are fuelling the rapid development of the new field of computational social science. To investigate user attention to the Hurricane Sandy disaster in 2012, we analyze data from Flickr, a popular website for sharing personal photographs. In this case study, we find that the number of photos taken and subsequently uploaded to Flickr with titles, descriptions or tags related to Hurricane Sandy bears a striking correlation to the atmospheric pressure in the US state New Jersey during this period. Appropriate leverage of such information could be useful to policy makers and others charged with emergency crisis management.


The dynamics of attention in social media tend to obey power laws. Attention concentrates on a relatively small number of popular items and neglecting the vast majority of content produced by the crowd. Although popularity can be an indication of the perceived value of an item within its community, previous research has hinted to the fact that popularity is distinct from intrinsic quality. As a result, content with low visibility but high quality lurks in the tail of the popularity distribution. This phenomenon can be particularly evident in the case of photo-sharing communities, where valuable photographers who are not highly engaged in online social interactions contribute with high-quality pictures that remain unseen. We propose to use a computer vision method to surface beautiful pictures from the immense pool of near-zero-popularity items, and we test it on a large dataset of creative-commons photos on Flickr. By gathering a large crowdsourced ground truth of aesthetics scores for Flickr images, we show that our method retrieves photos whose median perceived beauty score is equal to the most popular ones, and whose average is lower by only 1.5%.


We decided to make available to the scientific community the dataset we collected for the study in order to guarantee the reproducibility of the results and support future works in the field of computational aesthetics.


Flickr was once the leading source of photography on the internet, but has long since been displaced by Facebook, Instagram, Imgur and other competitors. The primary goal of this case study was to find ways to improve Flickr's user experience in order to increase its competitiveness in an oversaturated market of photo sharing sites.


Sometimes a researcher wants to study one specific person or event. A case study is an in-depth analysis of a single event, situation, or individual. To conduct a case study, a researcher examines existing sources like documents and archival records, conducts interviews, or engages in direct observation and even participant observation, if possible.


Researchers might use this method to study a single case of, for example, a foster child, drug lord, cancer patient, criminal, or rape victim. However, a major criticism of the case study method is that a developed study of a single case, while offering depth on a topic, does not provide broad enough evidence to form a generalized conclusion. In other words, it is difficult to make universal claims based on just one person, since one person does not verify a pattern. This is why most sociologists do not use case studies as a primary research method.


In this article, we will explore, 1) the history of Flickr, 2) the purpose of Flickr, 3) the benefits of Flickr, 4) setting up a Flickr account, 5) using Flickr for Business, 6) Flickr terminology, and 7) best practices/case study.


  • There's so much buzz around Flickr right now it's practically deafening. Or maybe I should say blinding, because Flickr is a collaborative photo sharing service. I was perplexed why Yet Another Photo Sharing Website was so hot until I started browsing the myriad hacks and tools available for this site. Flickr has a web API, and there's a .NET wrapper around that API available at Flickr.NET. It's truly astonishing; a case study in what having an open API and community-driven content can do for your business. Here are some of the cooler Flickr hacks (warning-- heavy use of Flash ahead)Flickr color picker. Shows all pictures for any given color you click in the color wheel. Quite mesmerizing.Flickr postcard browser. Photos are "tagged" in Flickr with various descriptive words by the users. This is a quick way to browse around a specific tag.Flickr related tag browser. This is like the postcard browser, but it also shows related tags that are frequently associated with whatever tag you're browsing in a ring around the pictures. Fantastic for browsing around and getting a sense of what tags are in use.FlickrGraph. Flickr also contains social networks-- users who mark each other's photos as "favorites". This tool lets you map out the relationships between users in graphical form.Flickr Replacer. A neat bookmarklet that takes any highlighted word on the web page and replaces it with an image representing that word (via tags, of course). Perfect for getting your rebus on.Spell with Flickr. Spells a word of your choice using Flickr images representing each of the letters.

As you can see from the above sampling, Flickr is all about tags. There's a neat page on Flickr that shows the most popular tags at any given moment.Amateur photographers take far better pictures, on the whole, than I could have ever possibly imagined. After seeing this, who needs professional photographers? Still, there's a big gap between the good and great pictures. My biggest frustration with flickr is that there's no rating system for the pictures. You can only browse pictures by user, or by keyword. I have a hard time coming up with tag keywords (frogs? dogs? clouds? graffiti?), and I don't really know any Flickr users. I'd rather just subscribe to some feed of highly rated pictures. Sort of an AmIHOTorNOT for photos, but hopefully without the prurience and desperation.This is, of course, only the tip of the iceberg. There's an exhaustive list of all the Flickr hacks at The Great Flickr Tools Collection. 2ff7e9595c


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