Method Reflection Sample
1.Read About HGSE first, we are doing this project for HGSE
2.Read Literature Review , SWOT and Research Proposal_draft2 to get a sense of what our theories are. Especially the part of Methodology, to understand that we gonna do a Network Analysis& User Roles, and Tweet content analysis for this topic.
3.Go through #8 Research elements & design II_survey Powerpoint, you might need that to d method reflection.
4. Hashtag we might use to collect tweets data:
1) #EdChat
2) #EdLeaders
3) #Edu
4) #Education
5) #Educhat
Assignment is: You may wanna see the EM777 study guide for the concepts of different statistical analysis methods and statistics.
1.Select two hypotheses that your group is working on. In your own words, explain what statistical analysis you would use to test each of the hypotheses AND why. Make sure to discuss how each variable was measured in your justification for that analysis.
Our 4 major variables: Topic, user type, leadership, public sphere or non-public sphere
The leadership and status in affinity spaces, we would argue, parallels opinion leadership in the two step flow of information theory. In affinity spaces, this leadership position is highly flexible, so we propose the first hypothesis:
Hypothesis1: Opinion leadership will change over time and based on topic of discussion in educator affinity spaces on Twitter.
As stated, affinity spaces provide an opportunity for the extensive intermingling of roles and statuses to share resources and knowledge. This leads us to our second hypothesis:
Hypothesis2: Opinion leadership will not be directly related to users’ social status (principle, teacher, researcher, caregiver, etc.) outside of the affinity space.
2. Provide all other statistics you will need to report when you write up the analysis (e.g., test statistic, effect size, significance, mean, standard deviation, regression, hypothesis testing, sample size determination).
Method Reflection
Hypothesis1: Opinion leadership will change over time and based on topic of discussion in educator affinity spaces on Twitter.
As stated, affinity spaces provide an opportunity for the extensive intermingling of roles and statuses to share resources and knowledge. This leads us to our second hypothesis:
Hypothesis2: Opinion leadership will not be directly related to users’ social status (principle, teacher, researcher, caregiver, etc.) outside of the affinity space.
Professional Education at the Harvard Graduate School of Education (HGSE) serves more than 10,000 educators around the world each year through a robust portfolio of 100 programs for early childhood, K-12, and higher education professionals.
Under hypothesis 1, the variables are topic and leadership. The frequency of topics of conversation changes is one measure to analyze how and what the participants are on talking about. Hashtags are standardized keywords, topics, or search terms where the participants' tweet and retweet various tweets on the same topic. Leadership can be evaluated by considering reputation and level of engagement. In the affinity space, if the educators influence others’ more often then there are likely to the opinion leaders and frequency of engagement including retweets.
The variables are user types (principle, teacher, researcher, caregiver, etc.) and public sphere or non-public sphere. The user type is the participant category that reflects the role of the participants. This is determined from the participant profiles with users categorized according to their roles. The proportion of each of the user types is determined after categorizing the users. Rosenberg et al. 20136 used an R script to collects data from user-profiles and then categorized the educators after first testing whether the rating was accurate. A hashtag-based space is public when it is open to different education stakeholders and as the hashtags are visible to all then this is a public space and vice versa. The level of engagement through tweets and retweets, the active weeks, and the tweets per participant are evaluated to determine how the users are using the public sphere.
Method
This is a quantitative content analysis and social media analysis using Twitter messages focusing on whether opinion leadership changes based on the topic of discussions in education spaces and whether it is linked to use and social status. The content ana...