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highest number of traffic tweets in relation to the proportion of the
city’s population. e status in Vancouver was similar. Montreal had
the lowest number of traffic-related tweets, showing that its citizens
were not really concerned about traffic-related issues.
Sentiment analysis provides valuable information to city officials
to prioritize the matters that require immediate attention and make
judicious use of available resources and funds to tackle such concerns.
e example that follows sheds light on the importance of sentiment
analysis for city officials.
6.3.4 Spain Uses Sentiment Analysis to Track and
Improve Standards of City Services
e city of Madrid has added a new feedback mechanism to its social
media networks. is mechanism provides options to citizens to give
their feedback and comments on various public services in the city
such as lighting, irrigation, waste management, and so on. City offi-
cials are planning to use this feedback to improve their services and
prioritize aspects that demand immediate attention.
6.3.5 Sentiment Analysis to Track the Mood of City Residents
Sentiment analysis can be used to track food habits, which in turn can
be used to track the mood of residents with regard to their food.
6.3.6 FoodMood.in Uses Sentiment Analysis to Track Food Mood of Citizens
FoodMood.in is a website that has the capability to combine tweets
with geographic locations to predict the present state of mind of citi-
zens with regard to food. Foodmood uses a sentiment classification
tool of Stanford University that is a “trained” classifier that can accept
millions of tweets as inputs at a time. is website also provides fea-
tures to classify top 10 favorite foods of a specific city or region. In
addition, it has options to compare countries based on their gross
domestic product (GDP) and food score.
Bristol University in the United Kingdom gathers the emotions
that are expressed in tweets to generate reports about the mood of the
country. is report has proved to be very accurate in its calculation,
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as it has been found that many times when there were riots and natu-
ral calamities in the United Kingdom, fear and sorrow were the emo-
tions that emerged as the general mood of the country.
6.3.7 Smart Policing Using Sensors and Domain Awareness System
e New York Police Department (NYPD) implements smart polic-
ing by combining sensor data with social media data. is solution was
developed by Microsoft and is called the Domain Awareness Solution. It
aggregates data from multiple sources such as video feeds, license plate
information, witness reports, and social media networks. is solution
provides investigators in the NYPD a real-time view of the criminal activ-
ity in the city. is solution also provides insights on potential threats.
6.3.8 Case Study of Sentiment Analysis Implementation in an Intelligent City
e city of Santander in Spain is in the process of creating a large
intelligent city. Several pilot projects are being implemented in this
city [4]. Smart Santander proposes a unique city-scale experimental
research facility in support of typical applications and services for an
intelligent city. is facility will be sufficiently large, open, and flex-
ible to enable horizontal and vertical federation with other experi-
mental facilities and stimulates development of new applications by
users of various types including experimental advanced research on
IoT technologies and realistic assessment of users’ acceptability tests.
e project envisions the deployment of 20,000 sensors in Belgrade,
Guildford, Lübeck, and Santander (12,000), exploiting a large variety
of technologies. A mobile application was developed for the residents
of the city. is mobile application has a tool to display the different
types of emotions at the Santander area. e six primary emotions
that are included in this mobile application are the following:
• Anger
• Disgust
• Fear
• Joy
• Sadness
• Surprise
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INTELLIGENT CITIES
• Ange
r
• Surprise
• Fear
• Disgust
• Sadness
• Joy
When the citizens of this city post messages to social media net-
works with the help of this mobile application, they can add appropri-
ate emotion-related color to their post at an appropriate location in
Santander. is helps to track sentiments of the citizens at various
locations in Santander.
6.4 Conclusion
Social media analytics is a niche and fast growing variant of analyt-
ics that focuses on the application of analytics on the data that are
gathered from the social media networks. e patterns that are gath-
ered as an outcome of social media analytics have diverse applica-
tions in various fields. e metrics to assess the impact of social media
networks were examined in this chapter. e key use cases of social
media analytics were discussed: customer relationship and customer
experience management, innovation, marketing communication pro-
grams, sales and lead generation, and brand advocacy. e different
types of social media tools and some market leading vendors for social
media analytics tools were also discussed.
In the next section of the chapter, the key focus was on the use
of social media analytics for the various services of city government.
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Asocial media architecture for intelligent cities together with a value
chain that specifies the value of social media analytics for intelligent
cities was discussed. A variant of social media analytics called senti-
ment analysis is very useful for city government to track and under-
stand the sentiments of citizens toward various decisions of the city
government. Various real-life examples that depict the use sentiment
analysis for various aspects of the city were also discussed. e chapter
concluded with a short case study of sentiment analysis implementa-
tion in an intelligent city.
References
1. Altimeter Group (2011). A Framework for Social Analytics (white
paper).
2. Bing Liu (2012). Sentiment Analysis and Opinion Mining. Morgan &
Claypool.
3. http://www.ibm.com/news/ca/en/2013/04/02/r881108u46877w41.html.
4. http://www.smartsantander.eu/.
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