Does #MotivationMonday result in better life habits?
Throughout the past two weeks I have pondered to myself the effects that tweeting with the hashtag #MotivationMonday had on people and whether or not their tweets resulted in personal success. Specifically, I invested myself in figuring out what emotions people portrayed with their tweets, their motives, and if the tweet was positive or negative.
How did we gather information?
I have always wanted to look at #MotivationMonday to see if people use it to continue to push themselves, or if they use it as a starting point in an activity. First, I used the TAGS software to capture tweets with the hashtag. tweets with the hashtag. To minimize there being too many tweets, I decided to limit the number of tweets found to 30,000. In reality, I only got around 90 tweets that I was able to use towards my study. The first step I took was just to read the tweets and get familiar with them.
Methods
As I first gathered the tweets, I tried to make sense of them. Some questions I asked myself included: "What are the goals of the people tweeting," and "Are they using the tweets to explain to people what they have accomplished with their day?". After making sense of the tweets, I quickly realized the categories I was going to sort through. Figuring out the emotion of people tweeting was important to me, as well as their motive for the tweet. The first question I asked was to see if the tweet was positive or negative. After I gathered all the information, I started trying to figure out what the results meant.
Results
The information I recieved from this picture was the most suprising of all the graphs I collected. I thought, from the beginning, people were going to use #MondayMotivation to Inspire people to start their week off right by using the gym. Around 37 people used #MotivationMonday to inform others. Whether it was on shopping deals, or gyms near them, it was the most popular. On the other hand, suprising to me, only 20 people used #MotivationMonday to inspire.
I was shocked that many of the tweets were about shopping deals or events of peoples everyday lives. One part of the graph that I found interesting but expected was that #MondayMotivation is a positive hashtag that inspires and uplifts, but is not a hashtag used to bring people down. Mostly everybody's motive was something positive rather than negative.
The graph I was most looking foward to making was the graph on emotions. I expected the feeling behind their tweets to be positive, which they were. The way I came up with the categories was thinking about how I would feel before delivering a #MotivationMonday tweet.
The two top emotions, kindness (27) and anticipation (22), were very expected. People who put out #MotivationMonday are trying to help drive themselves to workout, or help motivate others if they have already worked out. I personally thought that there would be more excited tweets on the topic, because they used the hashtag to motivate themselves. Lastly, I never thought that trust would be a category. Although only one person used Twitter to gain trust from users so they could motivate themselves to workout, it was interesting to see the unexpected emotion in the results.
I added this graph because the results were the least suprising of all the information. The majority of users chose #MondayMotivation because they wanted a great way to start their week. #MotivationMonday is not used to shine a negative light. The only suprising part was that around 44% of the tweets weren't positive or negative, they were merely focused on motivating people with shopping deals. On the other hand, expectedly 48.1% of the tweets were positive.
Analyzing Specific Tweets
Although this is a very simple tweet, it goes a long way. The tweet includes a picture that explains, "The Journey is about being more deeply involved in life and less attached to it". LoAnne Rissler's tweet perfectly exemplifies what I understood as a whole with #MotivationMonday. I categorized this tweet as being positive and inspiring. The tweet motivates people to start from wherever they are and try to work towards a goal.
This was one of the most suprising aspects of the project. I did not expect almost half of the tweets to be about shopping and deals. I am not sure why but this was a majority of the tweets. In this example by Evalina Dexter, she advises that people should use the picture on the tweet to get buisiness opportunities. A surprising amount of tweets were spam. Although it did not affect the study, it is unexpected how many tweets were spam.
Conclusion
In class there was much discussion about what it meant to analyze tweets. To me, it was exactly what I did. I found something interesting to me, and collected numerous tweets. After I went through them and looked for specific words and phrases within the tweet, I was ready to make an assumption on the data I collected. The conclusion I came up with was the tweets were more positive and I could have used a more successful hashtag. One conclusion that I can draw is that I should have used #MotivationalMonday instead of #MotivationMonday. Although I gained many results, I think if I used #MotivationalMonday the results would have been more geared towards life goals and accomplishments rather than deals on the internet.