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Last night I had a great time listening to Marc Davis, Chief Scientist of Yahoo!, talking about the new developments that they have been cooking at Yahoo! However, the night was first started with two presentations from Idean, who also paid for the pints – thanks guys! So, where is all this free beer and good talks? At MobileMonday, which returned to the roots of where it all started – Molly Malone’s Irish bar in Helsinki.

Marc Davis at MobileMonday in Helsinki

Marc started his presentation of by outlining Yahoo!’s visions of how to combine social networking and mobile into something that is ubiquitous and easy to use and develop for. I’ve always viewed the mobile phone as very good tool for social networking. Of course, you can call your friends, but I’ve also been texting to them for over 10 years now by both SMS and email, nowadays I can do video calls from the mobile too. So how is that changing? Well, I guess it isn’t. We’re just adding more ways to communicate to the same device. Which, let’s face it, is not a mobile phone anymore, but the most personal computer you have.

Marc also told us about Australian Aboriginal tribe, the Achilpa. They carry a sacred pole with them all the time as they wander around the desert to find food and water. To them, the pole marks the center of the universe – Which is very convenient as they never get lost (unless the pole breaks). “Where ever you go, is the center of the universe. And your people are always with you.”

The mobile has definitely become our sacred pole. (What three things do you take with you always when you go outside your home?) If our modern pole breaks, or runs out of battery, we would be lost and without any contact to our people.

However, is it too easy to think that you are in contact with our friends and loved ones if you just check their Pulse? I sometimes think that we are becoming more and more like the people in Solaria, a world envisioned by Isaac Asimov. Solaria is a world that is extremely sparsely inhabited and the people never meet each other in person, only through holographic viewing systems. They even have strong phobia about meeting in person. Isn’t this the direction we are going? Soon all that is required is to broadcast yourself and read the Pulse of your friends? And, in the best or worst case – depending how you look at it, that Pulse is already filtered by some ingenious system that tells me what is important.
I hope not. However, even though it was very nice to go home and give my wife an old fashioned analog hug, I have to admit that I’ve been away from home so many times that to be able to send at least digital hugs is very welcome.

What about the bag of ideas? Well Marc gave a good presentation of new Yahoo! technologies, like BluePrint and Fire Eagle. Take a look, and I’m sure you will get some great ideas. I did.

Yesterday, the second floor of Molly Malones offered a nice and friendly environment for mobile people from all industries to connect with each others in the event organized by Mobile Monday (MoMo). The topic of the evening was Earning models in Mobile Entertainment, which is also an important question to many of our customers.

Our board member Alan Moore gave interesting insights into the big opportunity in utilizing the players with different roles in social networks. This topic is closely related to what we do here at Xtract for mobile operators and other customers.

Other speakers gave also fascinating presentations. Dr. Josef Noll from Norway spoke about privacy issues in entertainment business. He forecasted that privacy matters will be huge business in the future. Dr. Madanmohan Rao pointed out that in India, where Bollywood and cricket are the most popular forms of entertainment, the ones who will understand how to make money from mobile entertainment will earn a lot of money.

The place of yesterday’s event, Molly Malones in Helsinki, was also the place where the idea of MobileMonday was invented. The original founders of MoMo were present at the event and told about how no-one could believe at the beginning (Sep 2000) that eight years later MobileMonday events would be organized in tens of cities all over the world. It is exciting how a good concept, such as that of MobileMonday, has the power to spread all over the world, thanks to world-of-mouth and people networking with each other.

… is the topic of my master’s thesis for HUT . I use “possibly” when speaking of modeling affects from mobile user experience data, because I’ve gotten the feeling these last weeks that the “recognising affects”-part just might be the topic of my PhD Now roughly in the middle of my thesis, I give you a summary of what’s happened.

What field is this exactly?

The fields concerned are affective computing, behaviorism, personality psychology and social psychology.

What do I call “mobile user experience data”?

Tom Guarriello defines in his article “Experiencing Experience” the ultimate experience is a cluster of smaller experiences. Consequently, he continues that measuring the user experience is best attained when considering as many elements in the cluster as possible.
For example, if you would consider a romantic dinner, what makes it a great experience is the cluster: candles, the dim light, the flower, the view, the slow background music, the quietness and sharing it with the other person? Take one of these alone doesn’t make the romantic. Two, maybe a little. The more element the better the experience. This is an analogy to multimodality. The more the merrier. Multimodality should be at the core of accurate affect recognition models, as emotions are intrinsically multifaceted. Having multiple modalities not only brings the accuracy of triangulation, but also by not fusing the behavioral components of moods allows to present the emotional context and maybe help to draw other conclusions if complemented by other contextual information.

How do you recognise emotions?

Recognising the user’s emotions can be done through many modalities, the most popular ones being: heart rate, skin galvanic resistance, speech tones and patterns, facial expressions, body postures and self-report. But baring in mind the current mobile phones and that the goal, being to get as large amount of users as possible with as little trouble as possible, it wouldn’t make sense to collect that kind of data, so I am focusing mainly on behavior data. This will also give a lower accuracy in time, so considering the spectrum of affective phenomena (Fig. 1) with time as main differentiating variable, I will focus on moods rather than emotions. Privacy being a concern, it is essential to compute private data in the mobile phone at low processing and battery cost.

Fig.1: Spectrum of affective phenomena (from Oatly, 2006)

These phenomena can be categorized in:

• episodes of emotions (seconds)
• moods (from hours to weeks)
• emotional disorder (from months to years)
• personality traits (lifetime)

In the context of advertising and communication, moods give a good emotional context for mobile ad targeting and filtering.

How do you recognise personality traits?

There are 2 main theories of personality: Eysenck’s model of personality (P-E-N) and the Big Five personality traits. Both have are based on the concept that there are few (respectively 3 or 5) broad dimensions or factors to describe the personality. Two factors both models have in common is neuroticism (tendency to experience negative emotions) and extraversion (tendency to enjoy positive events, especially social events).

Data I am focusing on to recognise personality traits is mobile phone usage, communication behavior, mobile internet behavior and social networks characteristics.

General mobile phone usage:

• How much people personalise their phone (wallpaper and ringing-tones)
• Time spent playing with the phone

Communication behavior:

• The time spent making calls
• The amount of incoming calls
• Time spent sending and receiving SMS messages
• Preference of voice communication or messaging
• How many people are around the person when he speaks on the phone
• The time laps people take to respond to a missed call or SMS
• Speaks on the phone without headset while driving
• The amount of sent MMS
• How often one checks if he has missed any calls/SMSs

Internet behavior:

• Time spent on mobile Internet
• Time spent for social purpose
• Time spent searching

Social network characteristics:

• Size of social network
• Amount of contacts

Once personality traits are modeled, positive and negative moods could be extracted using relevant theories of personality (Gray, Eysenck or Newman) relating to mood, personality and behavior draw a positive correlation between extraversion and positive mood, and between neuroticism (emotional stability) and negative mood (Gomez, 2000).

Triggers to Negative mood:

• Frustrative nonreward (Gray)
• Punishment (Gray)
• Novelty (inversed) (Gray)
• Displeasure (Eysenck)

Triggers to Positive mood:

• Reward (Gray)
• Nonpunishment (Gray)
• Pleasure (Eysenck)

What could correspond to such stimuli for a mobile user?
= What makes you in a good / bad mood when you use your phone?

E.g.

• Out of credit = displeasure
• Often receiving happy smileys = pleasure, reward
• Calls not returned = frustrative nonreward
• Regularity in patterns (or entropy of life) = novelty

Google has published their mobile and social network platform plans during the last week. Not so many surprises.

OpenSocial is quite natural next move from a company that wants to collect a lot of data. Social networking platform is a valuable source of behavior and social network data. And it is much more than have one or two social sites. The main concept with mobile has similar objectives. Who will dominate mobile usage and social data in the future. And finally who will prevail in digital media marketing.

But is it so simple that one company can prevail all relevant data in the future. Is it even possible that one company can collect all data when there will be more and more data all the time everywhere? I believe they can collect a lot of data. But on the other hand I believe that the services and data will be much more de-centralized in the future.

Intelligence comes nearer users and user devices. Smart analytics, customer profiling, and social intelligence come also to terminals (PC or mobile). The best solution to challenge Google is not to try to collect more data, but to have more intelligence to utilize the data. And this kind of analytics and advertising solutions help media and mobile companies to challenge Google.

My son’s in the eighth grade. It is interesting to observe how these school children are influencing each other when it comes to choosing mobile phones and even mobile operators. In Sweden, when Vodafone was sold off to Telenor, they changed their logo colours from Vodafone red to Telenor blue. Telenor ran heavy and expensive campaigns on pretty much all types of media about this colour change. One of the girls in my son’s class said quite loudly in front of a bunch of her friends: “I don’t like blue, I like red better!” And within 3-4 months, most of the kids in that class, including my son, had mobile phones and subscriptions from the operator 3 who happens to have a reddish logo. Is this girl an Alpha User? You bet! And then my son went around saying that Nokia phones are not cool, they are for old people. In the last school event, I asked a few kids in the class what phones they have. They were all, either SonyEricsson, or Samsung. And that considering that Nokia overall has the biggest marketshare. This word of mouth seems to work both ways - for a product or service, as much as against it. Read: Children, School and Mobile Phones.