In data collection, some experts have talked about the case of over-reliance on public interviews in qualitative research, and suggested that the public should be more use of naturally occurring data around.
These data include social media posts, which is a new form of easy-to-access and publicly available data. Analysis of social media data can help identify local trends and global dialogue, and proven to be observed tsunamis and floods and other natural disasters, as well as very useful through the crisis period (such as the UK riots).
Collaboration conference via Twitter
Twitter is slowly use in academic and industry conferences, providing another channel for participation in the conference participants.
Many scholars in this regard was also a junior researcher, if the presenter can ask questions without feeling embarrassed, it would be a positive experience. The media also able to discuss the controversial topics and speakers in a cooperative manner.
Grace Hopper Conference # GHC14
In the following example, researchers will provide a discussion of the Twitter experience to Grace Hopper Conference in Phoenix, Arizona on October 2014.
At the time, the meeting attracted more than 8,000 women in computer work and study at the meeting did not know anyone under the premise, the researchers found that Twitter is using a different label # GHC14 meeting of conference participants and presenters to interact well method.
At the meeting, the issue raised by Microsoft CEO caused a controversy, he said that women should wait for karma to get the organization raise / promotion. At this point, Twitter through # GHC14 outbreak, online dialogue has changed significantly, provide a channel for participants to comment.
As the researchers are very interested in this dialogue, so did some analysis.
Capture Tweets
The first task is to capture data from Twitter. Chrome or IE, visit the Twitter network to display all posts with that topic. Then select a data set NCapture (blue button through the top of the browser).
Import Tweets
通过NVivo最新版中的从其他来源选项卡导入它。（ NVivo是一款支持混合研究方法的软件。它可以帮助您收集、整理和分析访谈、焦点小组讨论、问卷调查、音频等内容。全新的NVivo12更可协助您处理社交媒体和网页内容。NVivo强大的搜索、查询和可视化工具使您可以深入地分析您的数据。）
导入后，数据将显示为带有附加元数据的表。一键可收集18000条推文。除了注释字段外，所有其他字段都作为本质上定量的字段导入以用于比较，并且注释字段就像调查中的开放式文本，可以进行定性搜索和编码。
探索模式
使用NVivo分析社交媒体数据的好处在于，无需成为软件专家，您就可以立即开始探索大数据中的模式。
请单击打开的窗口右侧的图表选项卡，然后可以找到一系列显示数据趋势的图表。默认情况下，您可以查看帖子中使用最多的用户名。有922个帖子提及@GHC组织，而提及@satyanadella的人数相同。要使用@符号查看帖子，请双击图表中的条形图。
然后，通过转到新显示的图表功能区或通过右键单击菜单，选择选择数据以更改数据视图，以查看一段时间内引用的数量（推文/转推文）。可以轻松地在各种视图之间切换（按天，按周，按月，按年）。
很有意思的是，在萨蒂亚·纳德拉发表讲话的同一天发布了收集的18000条推文中的8854条。第二天，会议进行了6370条推文（会议结束后的第二天），对话继续进行。然后，这些推文开始逐渐消失。数据清楚地显示，在有争议的演讲前一天，Twitter的活动减少了（第9位只有465个帖子）。
然后，我们还可以查看每周发布的推文数量，其中绝大多数是在会议期间发布的（16618，而下周为1382）。
You can also view the data by time with a user name, create a visual matrix diagrams (similar to the output matrix coding queries) fundamentally. The segment shows another view of the data, which is mentioned @satyanadella 641 views October 10, is mentioned 641 times on 11 October. @ GHC is mentioned 489 times on October 10, is mentioned 347 times in November 11.
We can do more charts, but need to look at the label to the right of the map.
View Tweets come from
This shows the location of tweet's, and they say show homes when setting up the account.
Sydney also has 130 tweets, please note that those who are not listed in its position as a global, 1 located behind the map in the Arabian Peninsula (106 with this label).
Of course, you can also drill down into a specific position of tweets.
This is only a beginning, more action still needs further exploration of the researchers themselves.