Tabula - Discover Yourself

Journaling is a known tool for the betterment of mental health as an intervention tool associated with "decreased mental distress and increased well-being relative to baseline." Tabula Rasa is a simple journaling app designed to bring the practice of journaling to mobile devices, innovatively using IBM Cloud Tone Analyzer to help users track progress.


According to the National Institute of Health, for certain types of depression about 40% of cases go undiagnosed. This is a common trend in mood disorders, where societal stigmas have caused many people to ignore the warning signs they encounter in their day to day thoughts. Tabula Rasa is a journaling app that aims to analyze the deeper meaning behind what you write. Powered by IBM Cloud Tone Analyzer, we have a trained text analysis ML model that is designed to extract such metadata as concepts, entities, keywords, as well as categories and relationships. Using this information, positive and negative trends in mood can be reliably identified, allowing users to gain a better understanding of themselves. This product isn’t just designed to help those with potential mental disorders, it’s well known that journaling as a practice can help prioritize problems, fears, and concerns; allow one to recognize triggers and learn ways to better control them; and provide an opportunity for positive self-talk and identification of negative thoughts and behaviors. As such, anyone with the slightest bit of stress in their life can benefit from journaling. As author James Bishop explains, “you can monitor the patterns in your life and identify negative influences that you need to avoid”. A journal isn’t just documentation, it’s a “plan for wellness”. Tabula Rasa takes this concept of journaling one step further through the functionality an app can provide. Push notifications allow for reminders to write, ensuring that users have the opportunity to journal daily. Secure logins through the cloud allow for the sharing of data from device to device so users can journal anywhere, anytime. The Text Analysis allows for a deeper understanding of a user’s feelings, cluing them into what their writing conveys about their emotions. Especially for the current Covid situation where many are at home, now is an excellent opportunity to take steps to better understand our mental health. Tabula Rasa represents a step in this direction.

Control Flow

  1. User downloads the app
  2. User signs up
  3. User begins journal entry
  4. Text is sent to IBM Cloud Tone Analyzer for analysis
  5. Sentiment analysis result is returned
  6. Result is stored locally inside the app
  7. Cloud AutoBackup backs up all information to the cloud
  8. Result is formatted and displayed on Insights slide

Desired User Experience

Starts off with a simple sign up page that requires an email and password to get started. Sign in with Google feature is also available.

A home page that lets the user write in journal entries with the ability to add as many entries as they desire. The user is able to scroll through all their entries vertically.

An analysis slide providing the results of the AI sentiment analysis displays results to users.

Implementation Details

Look around the repository to see how we developed our app.

Android Studio

API Version: Pixel 3 API 21

We used Android Studio to develop our app and core functions through basic widgets. We worked with XML style files to create our simple UI, and linked them to Java files for object functionality through XML Object IDs.

We implemented the Tone Analyzer through a text box and a button that were programmed to begin the analysis. When the button is pressed in the app, it initiates a task which is assigned to “analyzer” that then runs through our scripts accessing the IBM Watson source data, thus providing the tone of the written passage.

Google Drive Auto Backup

Android has an Auto Backup API that allows developers to easily sync application files to a user's Google Drive, which we implemented in Tabula Rasa. We utilized it to allow for sign-in with a user's email, which means that the data can be saved and restored across multiple installs and devices.

IBM Cloud Tone Analyzer

We used IBM Cloud Tone Analyzer to perform our sentiment analysis tasks.


Resource List:

Major Bugs Encountered

When we first set up our login functionality, sign in wouldn't validate the correct email address. This puzzled us for a long while simply because we weren’t super used to working with login systems – the complex nature of the system allowed for many areas of potential error so we were lost as to what was going wrong. Eventually we were able to fix this bug through adding in a separate statement to handle authenticating emails. In addition, we found a conflicting statement in our code that we fixed. Another issue was after we managed to get the bulk of the journal functionality working. The journal would add random entries upon entering the app which would require the user to manually remove them. Fixing this bug ended up being pretty simple, simply requiring the removal of a redundant statement.

Future Directions

Tabula Rasa already has relatively solid functionality, but due to the nature of the hackathon the UI lacks polish and this might impede the impact of the app. Users would be more inclined to write out their thoughts in a more inviting setting and so the UI definitely needs some additional work. In addition, right now our implementation of the Text Analysis feels somewhat barebones compared to what we COULD implement given more time. It would be nice to have more insight into a user’s writing available to them and perhaps even a calendar that tracked their progress. Adding this sort of functionality would attract and retain more users, further increasing the social impact of our project.


Smyth, J. M., Johnson, J. A., Auer, B. J., Lehman, E., Talamo, G., & Sciamanna, C. N. (2018). Online Positive Affect Journaling in the Improvement of Mental Distress and Well-Being in General Medical Patients With Elevated Anxiety Symptoms: A Preliminary Randomized Controlled Trial. JMIR Mental Health, 5(4).

Williams, S. Z., Chung, G. S., & Muennig, P. A. (2017). Undiagnosed depression: A community diagnosis. SSM - Population Health, 3, 633–638.

Journaling for Mental Health—Health Encyclopedia—University of Rochester Medical Center. (n.d.). Retrieved April 19, 2020, from

Therese Borchard. (2009). 5 Reasons to Track Your Mood: James Bishop. //

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