Chapter 9: Social Media for Consumer Insights

Strengths and Weaknesses of The Chapter
Strengths: Chapter 9 thoroughly explains how important observational research is, it also discusses how recorded behavior is referenced for future evidence to give organizations a better approach on new trends.
Strengths: Discusses the different types of monitoring, tracking, and research design marketers implement in order to keep up with consumers and collect data
Weaknesses: It does not explain how primary research for social media can be used effectively for "nonresponse bias". Social media is based on participation, understanding these errors would have been more helpful.


Terminologies
This chapter also had a lot of terms I had never heard before such as:
Online echo:  refers to the duplication of conversation volume that usually occurs in social media. Online echo exists due to people who share content and tend to share it with more than one community.
Sampling Weights:  Are adjustment factors that apply to differences in probability of selection between cases in a sample.  In other words, sampling weights are a percentage of popularity depending on a social media site. For example, 9% of internet users use twitter but twitter generates over 60% of content that social media monitors.
Netnography: a rapidly growing research methodology that adapts ethnographic research to study of the communities that emerge through computer interactions.
Scraping:  The collection of conversations through social media
Fetching: scraped data that is in need of being cleansed in order to get rid of unnecessary formatting

SocialMention.com
After visiting socialmention.com I ran an analysis on a popular brand I currently use. The brand is called MAC and I decided to look up the name specifically instead of adding a tag. After researching this I found a lot of different links related to it such as pictures from other sites. However, most of them were from photobucket.com. I believe there was a sampling error from the data I received because the data was only collected from a small subset making some of the results I received wrong. This is concerning because it is hard to understand the results I got if they are not related to my search.

Youtube
After reviewing socialmention.com I looked at several videos on YouTube related to this brand. Most of these videos were user generated however, a few were related to corporate. Anytime I go on youtube I notice most of the comments are user generated. However, I was able to gain insight from reviewing these videos based on the opinions people had. As the chapter states, social media solely relies on participation, so the more conversations people interact in the more popular the video becomes, leading to more views. In all, everything is a chain reaction.

Here's a list of the videos I viewed:

https://www.youtube.com/watch?v=TyvR6KBOPP8
https://www.youtube.com/watch?v=zoEmHecXUmo
https://www.youtube.com/channel/UC9EwwCBwzWhGGlNJujnnnRA?v=EuUxM01jhxQ
https://www.youtube.com/watch?v=21Vn5Jjojck
https://www.youtube.com/watch?v=gdcpHo6zIs0
https://www.youtube.com/watch?v=02E_uq_OJ8w