Top 350+ Solved Social Media Analytics (SMA) MCQ Questions Answer
Q. All data we gather from Twitter is written in ____________ format
a. CSV
b. JSON
c. Key-Value
d. Java
Q. Mining social web is transforming curiosity into __________
a. Data
b. insights
c. Key-Value
d. information
Q. Twitter allows people to communicate with ________characters messages
a. 140
b. 120
c. 180
d. 100
Q. _____________do not require mutual acceptance of a connection between users.
a. Facebook
b. Twitter
c. LinkedIn
d. None of above
Q. Calculating simple frequencies applied to unstructured text(tweets) called as ___________
a. lexical diversity
b. sparse diversity
c. linear diversity
d. None of above
Q. Which are offline generated social media data sources?
a. telephone marketing and customer support
b. printed press
c. E-commerce
d. Both a and b
Q. The two ways of data gathering in social media analytics are and .
a. API ; web crawling
b. online ; offline
c. estimated data sources; factual data sources
d. None of these
Q. The total number of people who see your content is content is termed as .
a. impressions
b. reach
c. post
d. economic value
Q. Which platform uses the Graph API as the primary way to get data into and out of the platform?
a. Facebook
b. Twitter
c. Instagram
d. None of these
Q. What is amplification in social media metrics?
a. Total number of Audience Comments (or Replies) Per Post
b. Total number of Likes Per Post
c. Sum of Short and Long Term Revenue and Cost Savings
d. Total number of Shares or Clicks Per Post (or Video)
Q. Which are the types of visualization in social networks?
a. semantic and temporal
b. node-link representation and matrix representation
c. structural, semantic, temporal and statistical
d. None of these
Q. Which are the different layout mechanisms used for visualization of social networks?
a. Property-based Layouts and Spectral layouts
b. Radial layouts
c. Force-directed and Energy-based Layouts
d. All of the above
Q. Which are the most common data mining applications related to social networking sites?
a. Group detection and Recommendation systems
b. Data representation
c. Group profiling
d. Both a and c
Q. What is/are the input(s) to k-means clustering?
a. number of clusters
b. distance metric
c. feature vectors of instances
d. All of the above
Q. Which measure ranks nodes with more connections higher in terms of centrality?
a. Group Centrality
b. Degree Centrality
c. Eigenvector Centrality
d. None of the above