How Can It Help? For some researchers it became a good tone to combine both for conducting the surveys and the others refuse to accept that kind of practice, taking them as two various dimensions, two various philosophies that should not be mixed in the one study. Qualitative vs Quantitative Data Analysis But what are the differences between quantitative and qualitative data analysis that make them particularly good or bad for some kind of research?
Sadly execution and analysis of these new social media channels has been hobbled by old world thinking. When it comes to marketing because of the old world thinking from the worlds of sTelevision and Magazines, and when it comes to measurement because of the world of traditional web analytics.
Stale marketing or measurement thinking applied to them results in terribly sub optimal results for all involved. So in this post my hope is to share with you what is unique about measuring one such channel, Twitter. The blog post is also sprinkled with my own words of folksy wisdom as to how you should use the channel for maximum impact.
My new book Web Analytics Qualitive and quantitive method of social. An Ode to New Thinking: One common thing between the all tools in this post is that they were built by "outsiders". One of the things I love and adore about Twitter besides all that connection and conversation is how its open API has lit a fierce fire of innovation when it comes to analytics.
Anyone and their brother and ma-in-law can develop a tool, and they have! Much to the benefit of the rest of us. Perhaps the most beneficial thing to me is how much out of the box innovation this has brought. For example just look at traditional web analytics tools, there is absolutely no fresh thinking when it comes to Social Media Measurement.
Their constant focus is on "let's figure out how to collect and report ever more data and not bother with a truly immersive understanding of these channels and what makes them unique".
That mental model is, sadly, extremely clear in the metrics and analysis they provide with "twitter integrations".
While there is some stale thinking in the new twitter tools, most of them have a lot of fresh thinking from people untainted by Omniture or CoreMetrics or WebTrends or, ok ok ok, Google Analytics. I consider this massive proliferation of new thinking to be a gift from God.
To all of you developers who are toiling out there, you have my love and gratitude. In this post four twitter analysis tools that while not yet fully developed show sweet signs of: Truly understanding the medium and uniqueness of the channel and 2.
Are not just reporting "hits", rather coming up with clever metrics. Most twitter analytics tools just do data puking. They find numbers that can be computed and then proceed to puke at you as many as they can find, with wonton disregard of value being provided or outcomes being measured.
Here is one of the mild ones: You must pause and think: So what is this saying? What action can I take? Always, always, always ask that question when faced with tools that simply puke data out at you twitter or Google Analytics or whatever.
But as I mentioned at the start of the post one of the beauty of twitter's open API is that there are a few pockets of truly innovative thinking.
Here are some that I humbly believe look promising. Klout is a wonderful little tool that measures Klout Scorea proxy for "influence": It is easy to understand the market demand to boil things down to one number, but this is perhaps the least useful thing in Klout.
While on the surface they might seem useful, I am always suspicious of compound metrics. They can be subjective, inapplicable to many and efficiently hide the insights you need to understand what actions to take.
Klout measures a bunch of lovely metrics, specifically applicable to Twitter, that are grouped into four buckets: There are two lovely things about these computations.
The factors used are laid out as individual metrics making it easy for you understand the data and pick metrics that work for you.Through examples and exercises, this handy student guide teaches methods for sampling, data gathering, developing questionnaires, reliability and validity, and quantitative and qualitative Price: $ Qualitative Research is ideal for earlier phases of research projects while for the latter part of the research project, Quantitative Research is highly recommended.
Quantitative Research provides the researcher a clearer picture of what to expect in his research compared to Qualitative Research.
Research in social sciences largely depends on measurements and analysis and interpretation of numerical as well as non numerical data. Quantitative research methods focus on statistical approaches and qualitative methods are based on content analysis, comparative analysis, grounded theory, and interpretation (Strauss, ).
Oct 18, · Qualitative and quantitative research are the two main schools of research, and although they are often used in tandem, the benefits and disadvantages of each are hotly debated. Particularly in the social sciences, the merits of both qualitative and quantitative research are fought over, with intense views held on both sides of the argument.
Quantitative and qualitative methods in impact evaluation and measuring results i GSDRC Emerging Issues Research Service This Issues Paper was commissioned by the UK Department for International Development (DFID) through the Emerging Issues Research Service of the Governance and Social Development Resource Centre (GSDRC).
Social Research Methods: Qualitative and Quantitative Methods 7e is a highly regarded text that presents a comprehensive and balanced introduction to both qualitative and quantitative approaches to social research with an emphasis on the benefits of combining various approaches.