Download How Social Media Analytics is aiding the Political communication

How Social Media Analytics is aiding the
Political communication: An interesting
relationship between politics and analytics
I always get amazed when I think about the world before and after social media. I can’t think
of a single thing which is not impacted by social media and “Politics” is one of them.
Nowadays, almost every well-known politician or a political party has an active twitter or a
Facebook page with an objective to connect with people in a better way. In this blog, I will
talk about the importance of social media analytics in politics, current trends and finally wrap
up with popular tools used for the sentiment/content analysis and network analysis of data
extracted from social media.
According to a study led by the University of California, San Diego, about one third of a
million more people voted in the United States in 2010 because of a single Facebook
message on Election Day. This shows the power of social media on people. This trend is
catching up in emerging countries like India as well. Therefore, there is an emerging need to
continuously collect, monitor, analyze, summarize, and visualize politically relevant
information from social media. These activities are considered difficult tasks due to a large
numbers of different social media platforms as well as the large amount and complexity of
information and data. And this is where social media analytics comes to the rescue.
The very first step regarding data collection is to determine the sources of the data. With
skyrocketing growth in the user base in recent years, social network sites and micro
blogging services with their most prominent examples Facebook and Twitter offer a huge
amount of politically relevant user-generated content in an unprecedented scope. Both
Twitter and Facebook offer application programing interfaces (API) for data tracking. The
most frequently used API for Twitter are ‘‘Search API’’ and ‘‘Streaming API’’, while
Facebook’s ‘‘Graph API’’ allows programmers to conveniently track Wall postings (i.e.,
status updates and comments). We can also implement the functionality of network
visualization by means of the API provided by the open-source social network analysis
software ‘‘Gephi’’.
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The different approaches of data tracking for a political institution which depend on the
specific intentions of that institution can be explained as follows:
Self-involved: It is applicable when an individual politician or a political party want to know
explicitly how people are talking about them in social media. It includes collection of all
tweets, hashtags, posts, comments/likes etc on social media platform.
Keyword/topic-based: Here tweets as well as Facebook and blog postings that involve
keywords related to topics of interest can be tracked. To attain a high level of data
completeness, relevant keywords representing the topic of interest have to be carefully and
systematically chosen in advance. The broader the topic to be analyzed, the more keywords
should be taken into account.
Actor based: There are usually a number of actors who can be considered as more
influential or more popular than most other users. These actors are said to have the power
to influence opinion making processes. Therefore, politicians or political parties are also
interested in monitoring such important users in terms of their generated content. For that,
an actor-based tracking approach might be employed to track tweets, wall posts, etc.
Random/exploratory: Here, tracking approach is to randomly select one or several sets of
data (tweets, Facebook or blog postings) for different time periods for analysis. Based on
these random Social media and political communication datasets, particularly content
analysis might be conducted to identify major political topics and detect users’ opinions or
sentiment associated with those topics.
URL based: Given that social media platforms are widely used, among other purposes, to
disseminate information, particularly by means of posting URL, political actors might also
apply a URL-based approach to selectively track contents behind hyperlinks shared in
tweets, Facebook and blog postings. This might provide additional meaningful insights,
especially in case of tweets with a limited length of 140 characters.
Social Media Analytics Framework in political context
Popular tools used for social media analytics in politically relevant user generated
content:
a) Automated content analysis/text mining: WordStat, LIWC, General Inquirer, etc
b) Manual content analysis/text mining: ATLAS.ti, QDAMiner, The Ethnograph, etc.
c) Opinion mining/sentiment analysis: SentiStrength, PolArt, SentiWordNet, etc.
d) Social network analysis: Gephi, UCINET, Pajek, etc.