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Table of Contents

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Analysis of the Tag of Current Articles

Label the Current Articles

After browsing all the articles, our team decide to label them with four tags.

• They are Pandemic, Information, Science Popularization, Welfare respectively.
• And an article can have more than one tags. Then we focus on the tags factors that effect the articles propagation and attractiveness.

Current Distribution of Tags

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From the pie graph above, we can see the tags of pandemic and information occupy more than 80% of the articles. It is in accord with the current situation of the official account. In the upcoming future, the distribution of Pandemic will decrease. So Information tag might be the major one.

Tag's Contribution to Propagation

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After use the function of propagation, we get the propagation value of each article. And the parameter of the function is decided by the general cases. As is depicted in the graph, articles with Welfare tag have a obvious weaker propagation, while other tags' distributions are close. That shows the welfare activities weren't propagated well. And the community can't completely depend on the official account to publicize some welfare activities. The residents are reluctant to share the activity with others.

Tags Contribution to Attractiveness

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To weigh the attractiveness of each article, we curve some data because some days the users surged strangly. We guess that's because someone advertise the official account by person. So we ignore these data. As is shown in the bar chart, the articles with Pandemic tag are the most attractive, while the Science Popularization tag is the least. But that doesn't means the articles with Science Popularization tag will drive users away because they are the reletive values. In the future, the official account can push more articles about community welfare. That's what the residents want to see.

Results and Advice

By no means before 2023, the articles with Pandemic tag are the most popular ones and the residents are glad to share them. However, the offical account has to find its alternative right now. Or there will be a shortage of the content. The Information tag isn't attractive though it is a must. Maybe it can be improved in the aspect of expression. Few residents reckon that the Science Popularization tag is interesting but those who value them are more likely to share the Science Popularization articles with others. When it comes to the Welfare tag articles, that's what residents want to see. The account had better find more ways to promote their propagation. Or just put them in the striking place.

Anaylsis of Other Communities' Official Account in 2019

Meaning

To adapt the offcial account to the post-epidemic era, we collect some data of the accounts in 2019. That will be helpful to the future content.

Data

The Data come from three communities. They are 'Caoyang Comunity in Shanghai','Huayang Community in Chengdu' and 'Jiubao Community in Hangzhou'. All of them do well in the official account. We choose 30 articles of these account respectively in 2019. And we curve their data so that we can treat the reading fairly.

Tag

We label the 90 articles as well and summerize 7 different tags:news of community works,propogation of online and offline functions,activity news,residents life,information and appealing,propagation of Party,knowledge popularization.

Graphs

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By differentiating two graphs above, we can get the deviation of different tags.

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Results and Advice

Activity news is the most important resource for the account. But WXJS haven't pushed is.
Other communities like to push propagation of Party and knowledge popularization, but residents don't feel like reading them.
The rest of tags are good. The account can take them into consideration.

Explanation of the Result of Propagation and Reletive Attractiveness

Propogation Extend of a Single Article=(Rate of First hand Shareness)*15+Rate of Reading if delivered  

Attractiveness Extent of a Single Article=min((Followers After Reading)/(Reading of the Shared Articles),1)

I set an upper limit to this data because it is meaningless if the value is bigger than 100%.
There are 4 major combinations of tags and 4 tags, so we can use a four-equations system to solve the contribution of each tag.