Currently, the Internet is rampant with user generated content and personal documentation. Users upload their pictures to online photo sharing sites such as Flickr, post their activities to the micro-blogging platform Twitter, and track their “friends” and associations on social networking sites such as MySpace and Facebook. This is just an abbreviated list of the kind of dynamic connections individuals are making between their own personal lives and the Internet.
What MoodJar attempts to answer, is whether there is a place or use for entering pure emotions into this technological mix. MoodJar at its most fundamental level is a Web 2.0 tool that allows users to record their emotions over time. Its purpose is to provide a way for users to better understand the evolution of their own emotions.

The core existence of MoodJar is a website home base. Here, users can quickly make a mood entry. Each entry consists of a rating that is scaled form -4 to +4 with 0 being neutral. The scale is purposefully limited to create consistency in tracking over time. The second most important portion of each mood entry are tags – a comma delimited list of keywords associated with the given mood. Using a taxonomy system serves to make input quick and succinct, while making output meaningful and simple to comprehend. The last portion of the mood entry is a field where users can leave small notes or reminders about the mood they are entering.

The data input into MoodJar is accessible via the archive portion of the site. Here users can filter their moods by year, month or day. The archive provides a way for users to look for patterns and put their mood in context by streaming in other data from applications such as Flickr or Twitter.



Background
There are several preceding works which inspire the function, motivation and purpose of MoodJar. Each of the following projects serve as a foundation for both what has worked and what is still lacking in the arena of mood tracking software.

MoodViews - Developed by a team of researchers from the University of Amsterdam, MoodViews taps into the mood feature of Live Journal; they track global mood levels, attempt to predict moods and understand mood changes across entries.
One of the aspects I find most inspiring about MoodViews is their concentration on context in emotions. Using their tool Moodsignals (see Figure 1), they attempt to draw correlations between trends in moods and current events.
Where MoodJar differs from MoodViews is that their project is research based, aiming to visualize collected data. As a result – their results are presented in a dry and uninteresting way. Furthermore, their data is collected unknowingly from the LiveJournal users rather than based on participation.

We Feel Fine - As an “exploration of human emotion on a global scale,” We Feel Fine uses parsing technology to comb the Internet for blog posts containing the phrases “I feel” and “I am feeling,” Their algorithms then extract the emotion and its contextual surrounding. Along with the emotions, they also pull out information about the author such as age, gender and location. The results are displayed in a beautiful Flash interface (see Figure 2).
MoodJar take a lot inspiration from the stunning design and presentation of We Feel Fine’s project. However, like MoodViews, their data is also collected from the Internet, rather than input directly from users.

Moodstats – Created by digital development agency Cuban Council, Moodstats is a purchasable, downloadable application which allows users to track moods on their computer. Unlike the latter two projects Moodstats does rely on the voluntary input of users to track moods. Currently development on Moodstats is stagnant and has not been updated in the last five years.
I feel the design and methods of Moodstats are limited by the fact that the software must be downloaded and is not web based. Furthermore, their system only allows input once per day and they track multiple aspects of a users’s mood (see Figure 3). All of the latter, I believe, creates a cumbersome and inaccurate user experience.
Furthermore, I believe MoodJar expands on the concept of mood tracking laid out by Moodstats since it will provide context with other web services such as Flicker and Twitter.





Audience
MoodJar is built with a broad audience in mind, but it has potential to reach such a broad audience because it is universal in both design and concept. At its widest umbrella target, MoodJar is built for users who are comfortable with the Internet and are used to inputting information into the Web.

From there, MoodJar aims specifically at the following four categories.
The user seeking mental wellness and understanding -The first target audience speaks to the foundational concept and purpose of MoodJar. It’s common practice for psychologists and psychiatrics to have their patients keep a chart of their emotions and moods. Such tracking gives both the doctor and the patient more concrete data to get to the bottom of problems.
The user who is seeking mental wellness and / or understanding may enjoy the advantage of tracking their moods in a sophisticated interface with visual results – as opposed to a pen on paper chart.

The hyper connected Internet user - The hyper connected Internet user wakes up, rolls over and checks their Twitter feed. They take photos on their cell phone of the dish they just ordered at the new restaurant in town and then upload it straight to Flickr. They rigorously track their finances by tapping all their bank accounts and credit cards into the financial tracking website, Mint. They look forward to planning their next vacation or business trip just so they can add it to their Dopplr queue. The music they listen to on iTunes while they work is streamed live to their blog, which, of course, is updated frequently throughout the day.
The Hyper Connected Internet User enjoys seeing their daily life digitally chronicled on the web – and may also want add their emotions to the stream.

The dear diary user - Many successful social networks today, such as Live Journal, MySpace and Facebook have succeeded in part because not only are they a platform for connecting peers (and strangers) but also because they are an outlet for the overwhelming emotions faced by teenagers today. LiveJournal saw success in their implementation of a mood indicator for users. Each LiveJournal entry contains plenty of room for the user to explain how they’re feeling - yet they additionally provide the option to start or end each post with a succinct mood check-in.
The younger (or even older) user who takes comfort in expressing their emotions on the Internet may be interested in sharing their moods in a new and unique way.

The collective good user - Many Internet users enjoy participating in online groups and projects. Take for example the Flickr group titled “Lonely Tree” which showcases photos of trees standing alone, often in the middle of nowhere. Despite being a decidedly odd and niche project, the Lonely Tree group has 2,769 members and 10,919 photos.
Another example of collective participation is ZeFrank’s Letter Project that called for people to submit photos of themselves holding a letter. The submitted images were put into a Flash application, which gives users an input box where they can type. What they type is then displayed using the different letter images.
While the motivations for participation in such groups as Lonely Tree and The Letter Project is certainly interesting and probably varying – the point here is just that there is a motivation. Often times that motivation is just to see the collective result of a group.
People who are interested in participating in collective projects may want to track their emotions so that they can add to the total pool of emotions and see what data results, i.e. What’s the happiest time of day? State? Profession?.



Implementation
Methods of input
o Website
o iPhone (other mobile devices)*
o Text*
o E-mail*
o Twitter (using their @user feature)
o Flickr (using specific tags)*


Input fields
o Simple mood range: -4 to +4 with 0 being neutral
o A descriptive note (optional)
o Mood tags


Privacy options*
o Public - all data is open and accessible to everyone.
o Personal - Data is shared for site-wide statistics, but the data is never traced back to a specific user and notes are never shared.
o Super Private - Data is kept solely for the user and never seen or shared with anyone.

Personal Output
o Graphs
o Email digest (weekly / monthly)*
o Mood tag cloud (where more common moods are larger)
o Facebook App*

* Future features