This paper focuses on a specific type of recommender system, known as Social
Recommender System (SRS). SRS is based on the relationship among users. There are
basically two objectives of this paper.
1. How the gap between kernel theory and system design can be bridged via an
intermediate component, named as "Applied theoretical model"
2. By using this novel framework, how can the performance of SRS can be improved
Collaborative filtering systems associate sources based on similar consumption profiles.
While the Social-network-enhanced Recommendation systems have arisen from people
preferring what their friends like and the availability of open social networks because
evidences have shown that people trust more on the recommendations given by their
friends rather than automatically generated recommendations. This kind of SRS generates
more personalized recommendations. But studies have shown that social network based
recommendation systems are not much advantageous than Collaborative Filtering (CF)
except some specific cases like when user's ratings for a specific item are highly variable (i.e.
controversial items) or where the user's profile is highly sparse (i.e. cold start), in these
exceptional cases some improvements can be made. For enhancing the accuracy of
recommendation system, theoretical grounding for social relationships in SRS should be
evaluated.
There are two approaches for role of behavioral theory in system design. One approach is
interested in generalizing design principles and articulating them as theory, as well as in
testing and evaluation methods. While the other approach recognizes that design research
involves designs that are clearly driven by supporting (kernel) theories from related
disciplines.
Engineering has solved this problem and uses the example of wing design being based on
aerodynamics. While kernel theory has very minor role in Information System (IS) design
research. In the context of IS design, the field of human-computer interaction (HCI)
illustrates how knowledge of human cognitive processes can direct principles of humancomputer interaction design.
There are four major challenges in bridging the gap between kernel behavioral theories and
systems design
1. Difficulty in finding relevant kernel theories for a specific design problem;
Drawing on Walls et al (2004) they suggest that one of the problems here is the
disconnect between behavioral and design researchers.
2. Kernel theory scope is too narrow, with no single theory accounting for all constructs
relevant to a design problem.
3. Granularity of constructs in kernel theories doesn’t math requirements of design
problem.
4. Kernel theories specify the direction of effects, where design requires consideration
of the effects’ magnitude.
Card and Newell developed a new theory "engineering-style theory". They address these
problems by developing applied psychological theoretical models (called “engineering-style
theory”) rather than borrowing existing kernel theories. It’s from there that they design
interfaces. But the issue with that theory is that it was not a generically applicable theory,
it can be applied to only few low level design problems.
However, the authors think that the Card and Newell approach can provide some
benefit to design research. And essentially argue that this applied behavioral model can
be added in.
Using social recommender system's context some steps are defined that needed to be
applied while incorporating social or psychological theory into system design.
1. Determine whether the application of psychological or social theories is
warranted in a particular design problem; Suggests SRS is an obvious fit given the
large stream of literature from social theory. Authors suggest that the
collaboration in HCI and CSCW communities may serve as a model.
2. Survey the relevant theoretical domain to identify constructs that map well to
the design goals.
3. Specify an applied theoretical model that is based on kernel theories;
Identify factors that would be antecedents of the dependent variable in the
applied theoretical model and important to achieving the design goal. A mapping
between design factors and theory based constructs.
For understanding the recipient’s willingness to accept a source’s advice some theoretical
constructs are needed: profile similarity (employed in traditional CF), communication logs
(e-mail, instant messaging, etc.), and social network data. They suggest that the designrelated factors map onto several theoretical constructs: profile similarity maps onto
homophily, communication logs correspond to tie-strength, and social network data maps
onto the construct of trustworthiness.
Then authors took a survey of "advice taking literature" and found that cognitive homophily
(source-recipient relationship), tie strength (source-recipient relationship), and
competence- and benevolence-based trustworthiness (source characteristic) are the most
important variables.
Tie strength is a multi-dimensional construct; it characterizes the closeness (i.e., emotional
intensity) and time dimensions (i.e., duration and frequency) of a relationship between two
parties.
Trustworthiness is also a multi-dimensional concept. Three dimensions of trustworthiness:
benevolence (a trustee’s caring and motivation to act in the recipient’s interests), integrity
(a trustee’s honesty and promise keeping), and competence (ability of the trustee to do
whatever the recipient needs)
Homophily research has focused on two key dimensions: sociodemographic (e.g., race,
gender) and cognitive. This paper doesn't focus on socio-demographic homophily as it
doesn’t have any direct significant effect on user's choice of source.
On the basis of three main construct i.e. cognitive homophily, Tie strength and
Trustworthiness, a set of hypotheses are made. All these constructs are discussed separately
versus "willingness to accept advice" phenomenon.
Some design principles have been discussed like, what are Meta requirements, how it
should be organized, what is the process of associating a user to relevant resources. What is
Meta design, what are different types of Meta design and what their sources are? Different
testable design proposition
The model then is tested by 116 participants. First data analysis was done using the Partial
Least Squares (PLS) path-modeling algorithm, the result was fairly good. Then they
developed a simple model that included homophily as the single antecedent of willingness
to accept advice (WAA), and then added one relational construct at a time. It showed that
some constructs enhanced accuracy while others create noise and slow down the system
performance