Pan-Pacific Conference XXXIV. Designing New Business Models in Developing Economies

Anxiety Index is defined as the ratio of term
frequency (TF) of a concerned risk to co-occurrence
frequency of negative terms (COF N ). The negative
terms are counted based on words and semantic
orientations. This index considers the cognitive
assessment of a concerned risk, such as ‘radiation’.
Even if the crisis communication corpus were to
include numerous references to ‘radiation’ and
negative assessment terms were not great, people’s
anxiety levels for ‘radiation’ would be interpreted as
relatively low. On the other hand, even if the crisis
communication corpus were to include only a few
references to the term, an assessment with a greater
amount of negative terms would indicate that
anxiety levels about ‘radiation’ were relatively high.
Figure 2 shows the co-relationship between anxiety
and time. In this study, COFN with ‘radiation’ were
counted for each seven days. To analyze the corelationship
between anxiety and time, we applied
the Anxiety Index for anxiety variable y and set a
time-serious variable x 1(,..., 7) as a day. Thus,
the co-relationship could be stated formally as a
linear regression model. In the figure, the regression
coefficient of government (TEPCO) is 2:1493; it is
positive and its coefficient of determination (R2) is
over 0.8. That means government (TEPCO) anxiety
regarding ‘radiation’ increased as time passed. On
the other hand, Twitter’s regression coefficient was
negative, but its R 2 was low. It means the corelationship
between anxiety levels of Twitter users
and time was not significant.
5. Conclusion
This paper has proposed a methodology for
measuring anxiety in a disaster, based on corpus
linguistics and a combining of methods, including
TFIDF and COF. In the Great East Japan
Earthquake, Twitter played an important role in
crisis communication between disaster areas and
non-disaster areas in the early phase of the crisis.
Measurement of anxiety related to the disaster was
achieved by estimating the risk assessments of
TEPCO and Twitter users by using the Anxiety
Index, which was proposed in this paper as an
indicator of negative risk perceptions of people
regarding the Great East Japan Earthquake.
Comparing TEPCO’s announcements and the
Twitter corpus, anxiety expressed by the
government changed noticeably, while anxiety
levels of citizens did not show clear fluctuations.
This study can provide governmental agencies with
guidelines for issuing clear information about
disasters to reduce anxiety among the public.
Methodology of this study could have been
improved, however. First, the list of semantic
orientations used for determining if words were
negative or positive did not cover the whole word
set, so certain words (e.g., coined words, clipped
words, proper nouns, or dialects) that were used
considerably in Twitter were not verified. Second,
the proposed Anxiety Index considers only negative
terms; it should be improved to consider other
factors that influence anxiety and individual
language use patterns associated with daily use and
emergency use. Third, since the Twitter data
includes contextual information (e.g., location, time,
and individual language use patterns) and user
networks in retweets. It is necessary to broaden the
investigations to use such data regarding anxiety.
ACKNOWLEDGMENTS: This work was
supported by the Ministry of Education of the
Republic of Korea and the National Research
Foundation of Korea (NRF-2015S1A3A2046781)
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