Create a username and password exclusively for Instagram or you can use you Facebook information. Enter your name and email address. Entering your phone number is optional. Instagram will give you the option to connect with your friends on Facebook and also the contacts on your phone. If you choose to skip these steps Instagram will suggest some people to follow. Your account will have no activity if you do not follow other members. Click register or done
The easiest way to get your Instagram account going is to follow the friends you already have on Facebook or in your phone’s contact list. You can also search for people using their user name
Instagram uses little to no personal information about its users. The only privacy setting you have is the option to make your photos private. By default your photos will be set to public meaning anyone with an Instagram account will be able to view, comment, or like your photos. Also they will be able to follow you. If you set your profile to private only people following you (after they send you a request and you grant permission) will be able to see your photos. You can do this and other account management from the settings button from your profile page
To obtain a random sample of Instagram users and retrieve their public photos, we first got the IDs of users who had media (photos or videos) that appeared on Instagram’s publictimeline,whichdisplaysasubsetofInstagrammediathat was most popular at the moment. This process resulted in a set of 37 unique users. By careful examination of each user in this set, we found that these users were mostly celebrities (which may explain why their posts were popular). We then crawledtheIDsofboththeirfollowersandfriends,andlater mergedthesetwoliststoformoneunifiedlistthatcontained 95,343 unique seed users. Next, we built a random sample of regular active Instagram users using this seed user list. Specifically, we operationalized the notion of regular active users as those who are 1) not organizations, brands, or spammers, and 2) had at least 30 friends, 30 followers, and had posted at least 60 photos.2 In practice, we found 13,951 users (14.6% of the seed users) who satisfied those criteria, out of which we randomly selected 50 users and downloaded their profiles, 20 recent photos (note that we cannot randomly download photos due to the limitations of InstagramAPI),andtheirsocialnetwork(listsoffriendsandfollowers). We chose to sample only 50 users here since we are performing manual coding of their photos which is not feasible over large number of users. This dataset allows us to make predictions with a 95% confidence level and a 13% confidenceintervalfortypicalusers,accurateenoughforthe analysis in this paper (i.e., the sample is representative). 3.2 ContentCategoriesandCodingProcess To characterize the types of photos posted on Instagram we used a grounded approach to thematize and code (i.e., categorize) a sample of 200 photos from 1,000 photos we obtained(50usersby20photoperuser). Comingupwithgood meaningful content categories is known to be challenging, especially for images since they contain much richer features than text. Therefore, as an initial pass, we sought help fromcomputervisiontechniquestogetanoverviewofwhat categories exist in an efficient manner. Specifically, we first used the classical Scale Invariant Feature Transform (SIFT) algorithm (Lowe 1999) to detect and extract local discriminative features from photos in the sample. The feature vectors for photos are of 128 dimensions. Following the standard image vector quantization approach (i.e., SIFT feature clustering (Szeliski 2011)), we obtained the codebook vectors for each photo 3. Finally, we used k-means clustering to obtain 15 clusters of photos where the similarity between twophotosarecalculatedintermsofEuclideandistancebetween their codebook vectors. These clusters served as an initial set of our coding categories, where each photo belongs to only one category.
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