Objective Today there are several health and medical apps (mHealth) in app stores. Germany is the world's first country that introduced apps paid by the regular health insurance service. Even though breast cancer is the most common cancer in women, mHealth for breast cancer has been largely unexplored. Methods A total of 33 apps from two major mobile application marketplaces (Google Play Store/Android; App Store/iOS) have been selected for analysis. Results The app analysis shows that there are currently only 10 mHealth apps in German, which are specifically dedicated to breast cancer patients. The features of these apps fall into two categories: improvement of health literacy and indirect intervention. These apps can be used for all phases of the patient journey starting with the diagnosis. Conclusions mHealth apps have the potential to support the adherence of breast cancer patients. In order to exploit this future potential, the app quality, as well as the information about the available apps, must be urgently improved. Currently, it is very difficult both for laypersons and for doctors/other therapists to identify high-quality apps. Guidance from independent or governmental institutions would be helpful to further the digitalization in health care.

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In this article we show how fashion brands communicate with their follower on Instagram. We use a continuously update dataset of 68 brands, more than 300,000 posts and more than 40,000,000 comments. Starting with descriptive statistics, we uncover different behavior and success of the various brands. It turns out that there are patterns specific to luxury, mass-market and sportswear brands. Posting volume is extremely brand dependent as is the number of comments and the engagement of the community. Having understood the statistics, we turn to machine learning techniques to measure the response of the community via comments. Topic models help us understand the structure of their respective community and uncover insights regarding the response to campaigns. Having up-to-date content is essential for this kind of analysis, as the market is highly volatile. Furthermore, automatic data analysis is crucial to measure the success of campaigns and adjust them accordingly for maximum effect.

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