Helsinki Institute for Information Technology

About: Helsinki Institute for Information Technology is a facility organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Bayesian network. The organization has 630 authors who have published 1962 publications receiving 63426 citations.

InfoRadar: group and public messaging in the mobile context

Abstract: Previous research has sought to utilize everyday messaging metaphors, such as the notice board, in location-based messaging systems. Unfortunately, many of the restrictions associated with the metaphors have been unnecessarily reintroduced to interaction, and results from the previous field trials have been disheartening. InfoRadar builds on experiences with these systems by presenting improvements in user interface functionality and services. By providing a novel radar interface for accessing messages, desktop-like temporal storage for messages, location-independent message threading, filtering functionality, contextual audience addressing, multimedia messaging, social activity indicator, and voting, InfoRadar attempts to combine both public and in-group messaging into one system. A preliminary field trial indicates that location-based aspects may have a role in facilitating mobile communication, particularly when it comes to engaging in social interaction with unknown people.

Give Social Network Users the Privacy They Want

Abstract: Social Network Sites (SNS) are often characterized as a trade-off where users must give up privacy to gain social benefits. We investigated the alternative viewpoint that users gain the most benefits when SNSs give them the privacy they desire. Applying structural equation modeling to questionnaire data of 303 Facebook users, we examined the complex relationship between privacy and SNS benefits. We found that SNS users whose privacy desires were met reported higher levels of social connectedness (i.e., perceived relational closeness with others) than those who achieved less privacy than they desired. Social connectedness, in turn, played a pivotal role in building social capital (i.e., the benefits derived from relationships with others). These findings suggest that more openness may not always be better; SNSs should aim to achieve 'Privacy Fit' with user needs to enhance user experience and ensure sustained use.

Clustering Based Active Learning for Evolving Data Streams

Abstract: Data labeling is an expensive and time-consuming task. Choosing which labels to use is increasingly becoming important. In the active learning setting, a classifier is trained by asking for labels for only a small fraction of all instances. While many works exist that deal with this issue in non-streaming scenarios, few works exist in the data stream setting. In this paper we propose a new active learning approach for evolving data streams based on a pre-clustering step, for selecting the most informative instances for labeling. We consider a batch incremental setting: when a new batch arrives, first we cluster the examples, and then, we select the best instances to train the learner. The clustering approach allows to cover the whole data space avoiding to oversample examples from only few areas. We compare our method w.r.t. state of the art active learning strategies over real datasets. The results highlight the improvement in performance of our proposal. Experiments on parameter sensitivity are also reported.

Finding meaningful uses for context-aware technologies: the humanistic research strategy

Abstract: Human-computer interaction (HCI) is undergoing a paradigm change towards interaction that is contextually adapted to rich use situations taking place "beyond the desktop". Currently, however, there are only few successful applications of context-adapted HCI, arguably because use scenarios have not been based on holistic understanding of the society, users, and use situations. A humanistic research strategy, utilized at the Helsinki Institute for Information Technology, aims to structure the innovation and evaluation of scenarios for future technologies. Population trends and motivational needs are analyzed to recognize psycho-socially relevant design opportunities. Ethnography, ethnomethodology, bodystorming, and computer simulations of use situations are conducted to understand use situations. The goal of design is to empower users by supporting their autonomy and control. Three design cases illustrate the approach. The paper showcases an emerging framework for informed innovation of use potentials.