Last week I looked at frequency of variables for the month of December (below), today I am going to break down the categorical variables a little further to look at the major content of each category.
In this post I will break down Information Sharing, Solidarity/Community, Information Seeking, and Memory. I will not, however, look at Grievances or Memory as they made up only 8% and 1% of posts respectively, which is too small of a data pool for significant analysis.
I will begin with the largest category, Information Sharing, which 40% of the total posts were classified under:
The top 3 codes for Information Sharing are aid (26%), events (16%), and donations (15%). It is not at all surprising that events and donations appear as the second most frequent codes as in general there is a strong correlation between aid/events and aid/donation (as shown below where the larger the dot the more coded segments coincide).
In terms of subject matter the fact that aid and aid related posts were common is also not surprising for information sharing. The majority of information shared was done so with a purpose, to aid in rebuilding, to raise funds for rebuilding, to provide information about helpful services. What is, then surprising about the code frequencies for information sharing is that only 2% of posts have content that have to do with planning for the future. I would explain this by methodology in coding, although in hindsight I should have coded any posts that had to do with raising funds or seeking out services as planning for the future (because they were planning for the future of their homes), I only coded posts as planning for the future if the author made specific references to their actual future plans. The only other significant percentages of codes are resilience (10%), business (8%), and institutions (6%). I believe that the frequency of the business and institution codes can be explained by the goal of rebuilding, these institutions and businesses were the ones that were a good source of aid (weather donated aid or not). The percentage of codes having to do with resilience is also not surprising as the page in general tended to be rather positive. As mentioned earlier, grievances was the topic for only 8% of original posts; while there were more grievances in the codes, it still does not make up a large percentage. This low frequency of negativity can explain why posts had to do with more positive topics like resilience.
The next largest category is Solidarity/Community with 28%:
Unsurprisingly, the most frequent code that appeared under this variable is resilience. Resilience, in my opinion fits in the same category as solidarity so I would say the fact that it appears in 24% of codes is logical. Aid (22%) is the next largely appearing code. I find this to be rather interesting because, as discussed previously, while posts about solidarity/community were encouraging for the community as a whole, they were not as helpful as information based posts. However, the fact that many of these posts seem to contain much aid information, suggests that the page really acted as more of a community bulletin board for the sharing and consuming of vital information.
The next category I will examine is Information Seeking, which made up 21% of posts:
1/4 of the codes in the category if Information Seeking had to do with aid. This fact continues to perpetuate the idea of the page as a bulletin board for information. The next largest codes are donations (15%) and institutions (95%), which we previously discussed as items that go hand in hand with aid in one way or another. What is rather interesting is that 8% of codes had to do with damages and 7% with devastation. When I saw this data it initially struck me as seeming to contradict the analysis of the page as positive that I made in the Information Sharing section. Upon second thought, however, I realized that this makes since given that the people here are trying to gain information on how to fix their damaged properties.
Finally I am going to take a look at Contemporary Documentation, which accounts for 8% of posts:
The findings here are unsurprising in my opinion. As these consisted of statements of the situation people seemed to either be reporting on the damages (15%) or devastation (11%) done by the storm or the strength of the community (resilience 16%). Resilience posts also seem to coincide with talk of community events (13%). The rest of the codes pretty evenly dealt with the other topics, more so than the other major variable categories I have examined. I would contribute this more equal distribution again to the fact that these posts recorded what was happening without an evident purpose beyond that, so the equal distribution seems logical under that line of thought
In conclusion, an analysis of the majority of posts (those fitting under the 4 categories discussed) shows that this page tended to be a positive and encouraging venue for Long Beach residents and, more importantly, that the page was largely used as a bulletin board for community members to ask for and share helpful information on recovery. Furthermore, considering that 14,167 amount of people “liked” the Facebook page (note that some of the people who liked the page are not residents, however I judging by the posts and comments made I would assume that a large percentage of people are residents) and that the population of Long Beach is only 33,400 people (Google) (some of whom do not use Facebook) it is a plausible claim that the page made a tremendous impact in aiding recovery by reaching such a large audience directly and, conceivably an even larger one indirectly.