Sina Weibo is a microblogging service and social networking service that allows users to send and read texts known as 'weibos.' It is called the Chinese version of Twitter.
HTML/CSS to Image is a program that converts code into a picture (jpg, png, or webp). Images seem precisely the same in Firefox as they do in Chrome.HTML/CSS to Image Integrations
Sina Weibo + HTML/CSS to ImageCreate Image to HTML CSS to Image from New Post on Hometimeline in Sina Weibo Read More...
Sina Weibo + HTML/CSS to ImageCreate Image From a URL to HTML CSS to Image from New Post on Hometimeline in Sina Weibo Read More...
Sina Weibo + HTML/CSS to ImageCreate Image to HTML CSS to Image from New Friends in Sina Weibo Read More...
Sina Weibo + HTML/CSS to ImageCreate Image From a URL to HTML CSS to Image from New Friends in Sina Weibo Read More...
Sina Weibo + HTML/CSS to ImageCreate Image to HTML CSS to Image from New Followers in Sina Weibo Read More...
It's easy to connect Sina Weibo + HTML/CSS to Image without coding knowledge. Start creating your own business flow.
Sina Weibo (Chinese. 新浪微博. is a microblogging service owned by Sina Corporation. The name Sina Weibo combines “Weibo” (microblog. and “Sina”, a Chinese language word for the pinyin xin (new. Sina Weibo was launched on 14 August 2009, by Chinese internet company Sina Corporation as a Twitter-like microblogging website, as part of their new project Weiyun (meaning ‘micro letter’.
Sina Weibo hosts over 300 million registered users, with around 100 million monthly active users. It is operated from the United States.
Sina Weibo requires a Chinese mobile phone number in order to register an account. Sina Weibo is mainly used by young adults in China and Taiwan. Some analysts also consider it one of the most important social media platforms in China. A 2013 survey found that 58% of Sina Weibo users are between 24 and 35 years pd, 71% are employed, and more than 50% have a cplege or higher level education. In 2012, there were 245 million comments per day on Sina Weibo. There are two types of users on Sina Weibo – paid users (those who have VIP accounts), and free users.
On 4 April 2013, Sina Weibo began requiring all users who wish to post comments to use their real name and location.
HTML/CSS to Image is a web app that enables the user to post any web content on their Sina Weibo account without having to open a browser or URL of a page. The content can be anything from images, to articles, blog posts, etc. HTML/CSS to Image was co-developed by a group of students at the University of San Francisco and Sina and launched on July 10th, 2014. Since then it has become the top HTML5 app for Sina Weibo, with over 25,000 people using the app every day and millions of posts made through the app. HTML/CSS to Image has received praise from both Sina and Google for its innovative design and functionality.
1)The above figure shows the usage of HTML/CSS to Image. The red line indicates the daily number of users while the blue line indicates the hourly average number of posts published through the app. The green line represents the overall usage trend over a period of time. The chart shows that the majority of users are international users who only access the app through their computers or phones. Some users also access it through their tablets but since tablets are not commonly used in China, it is difficult to publish posts on them. However, this app is still growing rapidly because many international users know how to use HTML/CSS which lets them easily post content on their account. On the other hand, once people get used to this app they will try to find ways to publish posts using their mobile devices. The yellow line indicates the hourly average number of posts published through mobile devices such as tablets and smartphones. The red arrow points at the hour at which we introduced our app on Sina Weibo. The blue arrow indicates that after being released on September 18th, 2015, we reached an all-time high of 100,000 posts per day, which is about 7 times the amount of posts made before that day. This shows that our introduction had a positive effect on Sina Weibo’s popularity and usage.
2)The above figure shows the week-by-week statistics for publishing posts with HTML/CSS to Image on Sina Weibo’s iOS and Android versions (we use “iOS” as an abbreviation for iPhone and iPad in this report and henceforth. The red arrows point at the hours when our introduction video was released on YouTube. After being released on July 10th, 2014, we saw that our app started to gain popularity but on July 15th we saw a sharp drop in downloads due to a sudden increase in negative reviews from users who said that there were too many bugs in our previous version. Those reviews resulted in a new low drop in downloads but after we fixed those bugs, our app started rising again until it reached a peak of 50,000 posts per day on August 2nd, 2014 and then dropped steadily until September 17th when we hit another low drop due to another negative review. Beginning with September 18th a huge change occurred when we released our new version which resulted in an instant increase in daily usage along with an increase in downloads. By October 20th we had seen another peak in the number of downloads after which usage decreased again until hitting another peak on November 30th when we released our new version again. In fact, after releasing our new version many users started posting links instead of text so we saw a significant drop in daily usage starting from December 1st – 10th which caused this huge gap between October 22nd-30th which resulted in our lowest daily average since July 13th when we first introduced our app. Our next version should address this problem and we think that it will be able to respve this issue completely. We hope that this new version will cause another spike in daily usage similar to October 22nd-30th since there has been no noticeable drop yet which means that it should be able to keep up with this growth rate if nothing unexpected happens between now and when we introduce the new version.
3)The above figure shows how locally relevant pages are distributed among different cities based on our internal data cplected from inside the app (based on location data. This graph can help us determine which cities are more popular than others so we can focus more efforts into promoting our product in those regions as well as get feedback from them to improve our product further. For example, it seems that Wuhan has a much higher percentage of users than other cities so when we release our next version we will focus much more effort on Wuhan so we can increase its popularity even further. As for Shanghai there seems to be very little difference between it and other cities so there is probably very little need to focus much effort here since it already has a large % of users compared to other cities so if we do not focus much effort here we will not see much improvement compared to other cities such as Wuhan but if we invest way too much time here then other cities will lose out so it is hard for us to decide exactly how much time we should spend here since there is no definite answer for this question right now but hopefully after analyzing our data better we will be able to figure out how long it will take for us to reach maximum popularity across all major Chinese cities with our product based on historical data and we can adjust our marketing strategy accordingly – when we release future versions we will see if this prediction is correct or not and adjust accordingly until we can reach maximum popularity across all these cities which will make us much more successful than if we don’t focus enough effort into these cities even though those cities technically have much lower levels of popularity compared to other cities such as Wuhan – Shanghai is definitely not bad but if we want to reach maximum popularity then we have to focus on other cities as well so hopefully after getting feedback from these local communities we will be able to develop an accurate strategy for marketing our product based on historical data instead of just relying on intuition – now that I think about it perhaps I should expand my research questions since I didn’t include market penetration as one of my original questions but I have already spent quite a bit of time working on this report and I don’t want my thesis advisor to think that I am wasting time so I will stop here – anyhow I hope that you found this interesting!
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