Greetings,

Normally any qualitative analysis program does the job directly. Consider NVivo and Sysmos, for example

Hi,

Have a look at the tutorial “Python for Communication Scientists: First Steps to Automated Content Analysis”, which can be retrieved from http://www.damiantrilling.net/downloads/py_for_cs.pdf

It pretty much tells you the start of how to 'crawl' or 'scrape' for data on social media, how you can process it and how you can use programs (usually self-written since there is no real existing software for this yet) to analyse big chunks of data. Also, there are multiple universities and courses around the world addressing this issue, usually called 'Big Data Analysis' or something similar (i.e. http://coursecatalogue.uva.nl/xmlpages/page/2014-2015-en/search-course/course/14792 at the UvA).

Martin Hawksey's TAGS is a great tool for harvesting tweets. It's simple to use and data is sent to a Google spreadsheet which can be downloaded as .xlsx 

It also has in built visualizations so you can see, for example, numbers of interactions and who has interacted with whom. 

I've written a little about my experience using it for the ascilite2014 conference.

I hope this helps.

http://sarahlibrarina.tumblr.com/post/103677547810/ascilite2014-a-social-media-journey-and-twitter

https://tags.hawksey.info/

http://ascilite2014.otago.ac.nz/

This thread is enlightening. I do many interviews off social media but had not even thought of doing this kind of research off media streams. I am glad these program are out other but so glad I do not do this kind of research.I use media for much research between other researchers and interviewees. I will stick to field research. I appreciate these posts because it was an area I did not keep up with.

Hi Victoria, 

We spent about 2 years to build an intelligent platform and technology to analyze social media and the rest of the web to detect anomalies and the trends in any given region. We call it "a bird's eye view" model. The platform released to public 1 month ago. You can learn more about the platform here: www.tilofy.com and I would be more than happy to give you free access to play with it and I would love to hear your feedback. Basically, our smart algorithms using machine learning and NLP to extract context from the offline world like a group of conversations from twitter or Instagram and analyze "whats happening in that given region in real-time". We have historical data for almost 1.5 years + real-time feed and our last phase is predictive model which is in progress. For example, if there is a marathon in LA today, Tilofy draws a heat map for you in real-time to see how the event evolve in the region and expand around the location. Basically, you can monitor the marathon from start to end in real-time and have access to all conversations, age, gender and race breakdown, sentiment, top influencers, pictures, videos, text, event start, pick time and end, tag cloud and taxonomy which determine other people interests about the same subject. All this information generating with the algorithms and is fully automated. I think it gives you a very good idea how big data can shine using Elastic Search, Ruby and Java!

Nvivo and NCapture could be of help.

Have you tried Principal Component Analysis or non-metric Multidimensional Scaling? 

@Dr. Muhammad Zubair Asghar,

Thank you for sharing these publications. I'll certainly be looking at those methods.

@Olga Buchel, thanks or the PCA tip.

@Emmanuel Mogaji, could you please expand on the NCapture capabilities?

Thank you, VR

Dear Colleagues and Friends from RG,

In my opinion, one of the best research methods that can be used to analyze the content of data in comments, posts, etc. on many pages of social media is sentiment analysis carried out on Big Data Analytics analytical and database platforms. More and more companies, banks and other entities need to carry out multi-criteria analyzes on large datasets downloaded from the Internet describing the markets in which they operate and contractors and clients with whom they cooperate. On the other hand, there are already specialized technology companies that offer this type of analytical services, prepare commissioned reports, which are the result of such multi-criteria analyzes of large data sets obtained from various websites and from entries and comments contained on social media portals. An important research technique that has been developing in recent years, the effects of which are used for the purposes of marketing activities of companies, is sentiment analysis carried out on large data sets collected in the Big Data database systems downloaded from the Internet.

As part of the processing of information collected in the Big Data database systems, the sentiment analysis is used very frequently during analytical processes conducted for the needs of scientific research. Sentiment analysis allows you to get an answer to the question, what is, for example, recognizability, what is the awareness, opinion on a specific topic among users of specific Internet portals, websites containing comments from Internet users, and social media portals.

In order to group the behavior of users of social media portals into specific classes of behavior, these classes must first be defined. Sentiment analysis using large data sets collected from entries and comments from social media portals and transferred to Big Data database platforms can be helpful. Then, when observing changes in certain types of behavior of users of social media portals, you can analyze the data collected in Big Data according to these observations. In addition, a useful tool can be an analysis of the behavior of users of social media portals based on current posts, entries and comments on specific social media pages, statistical analysis of comments on specific topics of posts.

This type of research is carried out by online technology companies that run social media portals and use the results of these studies to develop their viral marketing services, because this field of marketing is a key determinant of revenue generated by these companies from advertising sales on social media portals. The basis of marketing activities conducted in this way are market research conducted by collecting market data from the Internet regarding the offer of individual companies, their competition, demand for specific products and services from Internet users as well as collecting, processing and analyzing this data in Big Data Analytics database and analytical systems. . The process of collecting market data from specific websites can be improved by using 5G technology.

In view of the above, as part of the sentiment analysis carried out, large amounts of information downloaded from comments, entries, posts from social media portals are processed in Big Data database systems to determine, e.g. consumers' awareness of the products and services offered by specific companies. This type of information is of great importance for the purpose of planning advertising campaigns informing about the mission, idea, product offer, usability features of a given company's offer. This type of data may be relevant to forecasting changing consumer preferences for the offer of specific companies.

Currently, many research centers use sentiment analysis by examining the content of comments, posts and news of thousands or millions of users of social media portals and other websites. The sentiment analysis is carried out on large collections of information collected from the deliberately selected many websites and stored in Big Data database systems. This analysis is carried out periodically at specific time intervals to diagnose changes in the main trends of general social awareness, including opinions on specific topics in society. This analysis may also refer to the diagnosis of dominant political sympathies, specific political views and opinions on selected political topics. This analysis is also used to examine the public support at a given time for specific politicians, candidates in the presidential elections or parliamentary elections. If this type of sentiment analysis is carried out directly by presidential or parliamentary elections, then it can be treated as an additional research instrument of a prognostic nature. There were results obtained from this type of prognostic analyzes characterized by a high level of accuracy of prognostic research.

Do you agree with me on the above matter?

Please reply.

Thank you very much.

Best wishes.

Dariusz Prokopowicz