Juuso Karikoski

Diversity and End User Context in Smartphone Usage Sessions

Mobile end user context has gained increasing attention in the mobile services industry. Context information is seen as an important component in developing new, more personalized, mobile services and applications. This paper studies the effect of end user context on smart phone usage sessions. Smart phone usage sessions are used to depict user behavior and usage habits of smart phone users on a high level. We have detected end user contexts, and extracted smart phone usage session information from handset-based data of 140 smart phone users. We first examine and describe usage sessions as such, and then in different end user contexts. According to our usage session analysis, smart phone usage is highly diversified across users. For example, the average number of sessions per day ranges from 3 to 46. Characteristics of smart phone usage sessions differ in different end user contexts. For example, an average session is 37 % longer in the Home-context than in the Office-context, but Office has 56 % more sessions per time unit than Home. The results imply that mobile services and applications need to adapt to user behavior in order to be personalized enough, and that context awareness is indeed a worthwhile step towards this.

Contextual usage patterns in smartphone communication services

The mobile end user context has received a lot of attention from the mobile services industry lately. The location-based and context-sensitive information that are characteristic for smartphones can be utilized to study the use context of mobile end users. Accordingly, this article utilizes handset-based data in analyzing how the context of use affects the usage of smartphone communication services. The context is identified with an algorithm utilizing mobile network cell ID and WLAN data and resulting in five place-related contexts, namely Home, Office, Other meaningful, Elsewhere and Abroad. According to our analysis, voice calls are used least intensively in the Home context where the length of the voice calls is the longest, however. Email and SMS are used most intensively in the Office context, where the voice calls are the shortest in duration. Finally, mobile IM/VoIP and social media services are more free-time oriented as they are used most intensively in Elsewhere and Other meaningful contexts. The findings imply that people use smartphone communication services differently depending on the use context. However, context can be defined and identified in a number of ways, and this article presents only one solution that is highly dependent on the type of data collected.

Measuring social relations with multiple datasets

Because people have different levels of engagement with each other, measuring social relations is difficult. In this work, we propose a method of measuring social relations with multiple datasets and demonstrate the differences with empirical evidence. Our empirical findings demonstrate that people use different communication media channels differently. Therefore, we suggest that in order to understand social structures, one should use several kinds of data sources and not just depend on a single dataset. Our datasets include mobile phone data gathered with handset-based measurements and data from OtaSizzle online social media services. By means of social network analysis, we show that the online social media services have a different friendship network than the networks based on mobile phone communication. The mobile phone communication networks, however, have a very similar structure. These results are encouraging as previous research also indicates differences in the communication networks.

Spatiotemporal correlations of handset-based service usages

We study spatiotemporal correlations and temporal diversities of handset-based service usages by analyzing a dataset that includes detailed information about locations and service usages of 124 users over 16 months. By constructing the spatiotemporal trajectories of the users we detect several meaningful places or contexts for each one of them and show how the context affects the service usage patterns. We find that temporal patterns of service usages are bound to the typical weekly cycles of humans, yet they show maximal activities at different times. We first discuss their temporal correlations and then investigate the time-ordering behavior of communication services like calls being followed by the non-communication services like applications. We also find that the behavioral overlap network based on the clustering of temporal patterns is comparable to the communication network of users. Our approach provides a useful framework for handset-based data analysis and helps us to understand the complexities of information and communications technology enabled human behavior.

Substitution in smartphone communication services

Substitution between mobile internet communication services and traditional mobile operator-provided communication services is studied in this paper using smartphones. The empirical data are collected with handset-based measurements conducted in Finland between 2008 and 2010. The data are collected from a total of 183 early adopter Symbian smartphone users. The individual-level correlation analysis indicates that no clear evidence in favor of substitution can be found. This implies that the services are used for different purposes as independent services and are not direct substitutes to each other. The results support similar studies conducted by other researchers. However, the analysis can be extended and improved in a number of ways that are discussed as future research.

Handset-Based Data Collection Process and Participant Attitudes

Handset-based measurements are an emerging method for collecting behavioral data about smartphone users. Setting up these kinds of measurements is challenging because of the personal nature of the data collection device and a lack of standards related to behavioral data and the method as a whole. Privacy issues related to the participants of the data collection are of major importance when dealing with behavioral data. Introduced is the process of collecting handset-based data in the OtaSizzle project in the Aalto University community in Finland together with a literature review of other similar data collection efforts in academia and industry. A survey is also deployed to study the incentives for participation, privacy concern levels and innovativeness of the user group participating in the measurements. This article contributes to the body of knowledge regarding measurements conducted with smartphones and sheds light on participant attitudes about them.

Measuring Social Relations: Case OtaSizzle

There are different levels of engagement in social relations between persons. Using a single data set for measuring social relations may, however, lead to fallacious results, while using multiple data sets the threat of fallacy can be reduced and the nature of different kind of social relations examined. This paper presents the OtaSizzle research platform for combining multiple data sets and measuring social relations. To present the usefulness of this, the first empirical results of the social network analysis performed with the platform are presented and discussed. Handset-based measurements are used together with data from the OtaSizzle social media services to study the social relations within a group of 20 users. As a result the social networks derived with the different data sources are presented and compared and a number of future research items discussed. According to the measures calculated the social networks derived from the mobile devices are quite similar while the OtaSizzle service network is considerably different, indicating a difference in the online social network and the communication network inside the user group.

Characterizing Smartphone Usage: Diversity and End User Context

Mobile end user context has gained increasing attention in the mobile services industry. This article utilizes handset-based data, collected from 140 users, to examine smartphone usage in different place-related end user contexts. Smartphone usage is examined first on a high level by using smartphone usage session as a unit of analysis. Then the usage sessions are dismantled into application sessions for deeper analysis and application level study. According to the authors’ analysis, smartphone usage is highly diversified across users. For example, the daily smartphone usage time differs by orders of magnitude between users. They observed also that smartphones are used differently in different end user contexts. For example, some applications are clearly more context sensitive than others. The results imply that mobile services and applications need to adapt to user behavior in order to be personalized enough, and that context awareness can indeed be a worthwhile step towards this.

The effect of an individual's age on the perceived importance and usage intensity of communications services--A Bayesian Network analysis

Multiple novel interpersonal communications services have emerged recently, but how their usage and perceived importance are related to the personal characteristics of the users is still relatively unexplored. Therefore, the aim of this study is to explore the effect of an individual’s age on the perceived importance and usage intensity of communications services based on Bayesian Networks using a survey of 3008 Finns during 2011. In the case of Short Message Service (SMS), Instant Messaging (IM), Internet forums and communities (e.g., Facebook & Twitter), and e-mail the results indicate that the perceived importance of the communications services decreases as the age increases. With phone calls and letters, however, no clear dependencies with age were identified. In the causal analysis the importance of Internet forums and communities was the only variable which can be stated to be directly caused by an individual’s age. This variable also acts as a mediator in the path from age towards perceived importance of other communication services and also towards their usage intensity. These results about the central role of Internet forums and communities can be exploited, for example, by device manufacturers when designing their products, and by service providers when designing their consumer services. The study also provides new information for mobile operators about the dependencies between mobile communications services and a documented example workflow for research community to construct a causal Bayesian Network from a combination of observational data and domain expertise.

Building social capital with mobile communication services

People may use different kinds of mobile communication services depending on if they are communicating with, for instance, friends, acquaintances or strangers. Thus, in this paper bonding and bridging social capital is studied in the context of two mobile communication services, short message services SMSs and voice calls. In Granovetters terms, bridging social capital refers to communication with weak or absent ties, while bonding social capital refers to communication with strong ties. We find that both SMSs and voice calls are used for bonding and bridging social capital, but SMSs are used more for bonding purposes than voice calls. Furthermore, media multiplexity is more associated with bonding than bridging social capital. We also present a method for studying social capital in the context of other, newer mobile communication services, and present results of a pilot study. The implications of the results are discussed from a number of perspectives including communication research, social network analysis SNA and mobile operators.