5 Steps to Success with Social Media Data Analysis

mumpsimuspreviousAI and Robotics

Oct 25, 2013 (3 years and 9 months ago)

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5 Steps to Success with Social Media Data Analysis


Due to the rise of social media, communication and interaction has changed between people. Instead
of untraceable direct communication from one person to another, social media technologies allow
people
to simultaneously communicate with many people while leaving a digital record.

From a
business perspective, these communications provide almost endless insights.


These insights can be
used to learn more about customers, find behavioral patterns and trend
s, help understand what
different customers want, and in turn how to help businesses grow.

In this blog we will discuss they
key aspects of social media data analysis.

1. Collect social media data

Although this may seem the most obvious task of data analy
sis, it is the foundation to social media
data analysis.


Collect data from various social media such as internet forums, blogs, social networks,
micro
-
blogs, podcasts, or even videos. The goal is to study the opinions and behaviors to gain
insights of con
sumer behavior, marketing insights and product sentiment.

Context accuracy is an
important aspect of the data collected to be analyzed. Good Natural Language Processing (NLP) is
therefore a critical requirement of tools used to gather the social media data
.

2. Extract and track the flow of relevant information

Some of the basic units of information are pieces of information that propagate between users, media
sites, phrases, quotes, messages, links, and tags. The goal is to extract and track units of inform
ation
that correspond to each other or that have relation to what your consumers are talking about. Think
about brand names, product categories, industry jargon words, etc. While collecting data, make sure
to collect the right information and to collect it

properly, because it is vital to a sound social media
data analysis that one collects relevant information.

3. Correct for incomplete or missing data

It is important to look at the big picture when it comes to social media, but complete social media
data
is nearly impossible to collect and the data that is missing will bias the results. Social media data
analysis cannot just be computational output, it needs carefully analysis to track sources, add content,
and pull together trends.

4. Predict and model th
e flow of information

Some questions to ask:



How do messages spread through social networks?



How can the spread of information be predicted?



What “network effects” are crucial to spreading the word?

Identifying patterns in the flow of information and using

graphs and charts will help visualize
information to help strategic decision makers get a better understanding of the insights.


Providing an
online portal or “Dashboarding” of these insights and trends helps to disseminate social media data
analysis insi
ghts to entire organizations, and can help automate insight reporting.

5. Combine the social data with other data sources
-
triangulate!

Triangulating the social data with other forms of data provides significant additional power to the
actionability of the
data. Other data forms including behavioral data, qualitative and quantitative
primary research insights and syndicated data. These combinations further inform how if and how the
social activity generated an ROI.

6. Harness the insights and engage social m
edia

The true value of a social media data analysis comes in the execution of the strategy that the analysis
informs.


Revising social media campaigns, improving customer experiences, responding directly to
customer dissatisfaction, and much more can be ea
sily accomplished through social media data
analysis

Social media has changed the game. If your business needs help with social media data analysis or
you would like more information, please
contact

Silicon

Valley

Research

Group

or leave your
comments below.