Parks marketing scrapes and surveys citizen comments about a waterfront redesign. Which application pattern is that closest to?
Select an answer to reveal the explanation.
Short Explanation
Reading the room about a park redesign is sentiment work. Comments and surveys tell you how people feel, not how a pump vibrates. That is a classic monitoring pattern for civic communications.
Full Explanation
Consumer/citizen sentiment monitoring is a recognized Big Data application pattern. Parks programs combining scraped comments and survey text to gauge reaction to waterfront designs illustrate that civic pattern. Ethics and representativeness still matter when interpreting sentiment for public space decisions.
Calling the pattern machine-to-machine pump vibration monitoring fails by concept: comments and surveys are human sentiment sources, not pump M2M. Calling it HDFS block-replication tuning fails by concept: that is cluster operations, not an application pattern for citizen voice. Calling it mandatory predictive policing without ethics review fails by concept: parks sentiment is not an ethics-free policing mandate.
Exam caveat: Sentiment monitoring across comments and surveys is the pattern—distinct from M2M industrial monitoring, HDFS tuning, or unethical policing mandates.
Operational check: Combine scrape and survey sentiment with representativeness notes, disclose methods to the public, and refuse to treat social noise as a substitute for formal civic engagement where required. Document residual risk for civic operators and revisit after the next production change window.