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In Cooperation with Ing. Michal Novák and Ing. Jiří Přibil, Ph.D.
Expressing attitudes and opinions towards various entities (i.e. products, companies,
people and events) has become pervasive with the recent proliferation of social
media. Monitoring of what customers think is a key task for marketing research and
opinion surveys, while measuring customers’ preferences or media monitoring have
become a fundamental part of corporate activities. Most studies on automated
sentiment analysis focus on major languages (English, but also Chinese); minor or
morphologically rich languages are addressed rather sparsely. Moreover, to improve
the performance of machine-learning based classifiers, the models are often
complemented with language-dependent components (i.e. sentiment lexicons). Such
combined approaches provide a high level of accuracy but are limited to a single
language or a single thematic domain.
The team tries to contribute to this field and develops a model for sentiment analysis
utilizing just a language– and domain– independent components. The model has been
previously tested on multiple corpora, providing an acceptable trade-off between
generalization (language– and domain– independence) and the classification
performance. Furthermore, we would like to extend the model utilizing the
surrounding context (other documents in the same location – a thread or a discussion;
or other documents occurring in the same time frame) of the classified documents.
In Cooperation with Ing. Michal Novák
The impact of culture on consumer behavior has been researched for decades. Market
interdependence has prompted the emergence of theories, which attempt to explain
differences between markets. Studies of cultural differences introduced by Hall,
Hofstede or Trompenaars and Hampden-Turner have become the classics of
academic literature and the prominence of intercultural studies has survived or even
grown in research interest there are new theories and approaches emerging (i.e.
GLOBE study). Discussions about cultural specificity affected all components of
marketing mix, including online marketing. Web designers began reflecting and
adjusting to user‘s cultural characteristics. Internet customers are different across the
world according to their culture, however their online behavior can be similar in some
ways. Websites need to be culturally adapted, although several cultures incline to
adapt global patterns, behaviors or brands.
The team tries to contribute to this field in several ways. The first research area is on
the intersection of neuroscience and marketing. We try to utilize eye-tracking to
determine consumer’s visual attention over various stimuli. The aim is to distinguish
how various (not only cultural) user’s groups perceive the online environment and
discover what are the drivers of their behavior online. This could help the marketers
better communicate with customers from various countries and reflect local specifics
of the national markets.
We also cooperate with MindShare company – a global media agency network and
have access to Mindreader – s Mindshare’s proprietary study looking into digital
consumers from around the world. The dataset contains hundreds of questions
related to attitudes, interests, activities or concerns of respondents from 45 countries
around the world. Again, we try to uncover new findings which would help the
marketers better communicate with customers from various countries and reflect
local specifics of the national markets.