Seeing Theory: a visual introduction to probability and statistic is a fantastic resource for people who want more a bit more about one of the most useful aspect of our everyday lives.
Probability is everywhere, it governs our everyday lives, is extremely important for even casual decision-making. Still, like Daniel Kahneman pointed out in his wonderful book, we are incredibly bad at estimating statistics and making rational decisions based on data.
To make the situation a little bit better, go play with interactive exhibits on the Seeing Theory website. You would be able to learn more about important statistical concepts: from probability to ANOVA and regression.
An interesting insight into how much Americans are interested in different countries in the world. The map is based on the Google Trends search data:
Full article also compares the Google Trends data to news coverage data.
Yesterday I presented at the CeDEM 2016 conference in the Austrian town of Krems.
It is a great venue to get to know more people working in your field and just make friends.
On CeDEM16 I presented a paper of social media activism in Ukraine. It is kind of a followup to my earlier 2014 paper on similar topic. I’ve got nice feedback and as people are interested in the issue, I decided to share.
You can download my presentation. I included comments with every slide.
The full paper is available in the proceedings of the conference.
This is not a comprehensive review (although you’re welcome to add more sources in comments or send me an email). This is also not a real scientific literature review. Some results are contradictory and it is up to you to judge who is right and who is wrong.
This is just a list of academic papers/theses/articles published on the topic of Couchsurfing. I used many of these papers when I was writing my thesis and articles on CS. I hope this little review will help you in your research.
This post is also available in pdf.
(Adamic, Lauterbach, Teng, & Ackerman, 2011) combines data analysis of ratings, a large-scale survey, and in-depth interviews trying to understand the ratings on CS. Many users tend to overrate other members being afraid that they may provide reciprocally negative reference or rating. Negative references are underrepresented (only 1 to 2500 positives). Authors propose rating design that would encourage more balanced feedback.
(Ayers-Greenidge, 2012) explores guest’s motivations to use CS. Author finds that motivation to be a traveller (rather than tourist) is the most important, while initial motivation to save money when travelling is also popular. Author ties trust to the concept of intimate tourism. The similarity is an important factor in selecting possible host.
(Bialski & Batorski, 2010) ties concept of trust in CS to familiarity. Using an online survey of 3000 CS members, and 30 personal interviews, authors outline three stages of the CS experience when the trust emerges: pre-selection of users, website and profile navigation and offline contact. Familiarity plays crucial role in the formation of trust.
Continue reading Literature Review of Couchsurfing Research
Absolutely fabulous article about computer science concepts: 40 Key Computer Science Concepts Explained In Layman’s Terms
Highly recommended to anyone interested in the computer science and programming.
Journalysis is a website that collects reviews of the academic journals. Any registered user can add his or her review of a selected journal. In future that might become a useful tool for distinguishing low-quality journals.
Web services for proof-reading can be a powerful tool if you know where to trust them and where better not. They can help you make your own text simpler, more straightforward and concise by offering simple corrections and checking for very basic mistakes (like using the same verb in consecutive sentences or using adverbs where they are superfluous.
Here is a short list of such services working in your browser:
Grammarly: “Grammarly makes you a better writer by finding and correcting up to 10× more mistakes than your word processor.” Very popular and lauded service with huge number of users. Find grammatical mistakes, contextual spelling errors and also highlights poor word usage. Also offers Chrome browser integration.
Hemingway Editor: Much simpler service meant for short texts. “The Hemingway Editor will highlight (in yellow and red) where your writing is too dense. Try removing needless words or splitting the sentence into two. Your readers will thank you.” It also gives your text a “readability” score.
Pro Writing Aid: Another comprehensive service that creates a report about the quality of your writing. It checks for consistency, complexity, vague words and alliterations among other things. The downside is that it is much more cluttered compared to Grammarly and also not very usable in its free version.
Paper Rater: This service offers grammar checks as well as plagiarism detection. Function-wise it falls a bit short compared to Grammarly or ProWritingAid.
The question of whether this particular journal is to be trusted bugs me everytime I’m ready to submit a completed article.
It appears that many researchers have the same problem.
Here there are two excellent lists of journals not to be trusted and publishers with questionable practices (lists have respectable 507 and 693 entries). Ideally, one should think twice before submitting to any of the journals/publishers in these lists. Also there is a list for misleading journal metrics.
Jeffrey Beall created a neat list of criteria of a problematic journal. If a journal follows at least some of the mentioned practices, you’d better consider submitting your manuscript elsewhere.
Another interesting website calculates impact factor for journals you enter, it seems legit.
The question that is often asked in the SNA academic community is where a researcher can get ready datasets. As a prepared answer to such questions here is a short list of repositories of datasets for social network analysis.
- Stanford Large Network Dataset Collection (https://snap.stanford.edu/data/)
Perhaps one of the most famous SNA repositories. Includes huge datasets of Wikipedia, Twitter and Facebook data.
- KONECT (http://konect.uni-koblenz.de/)
Koblenz Network Collection contains 281 large network datasets of different types from various spheres. Good collection of authorship, coauthorship and citation networks.
- Corporate Elites (http://www.eelkeheemskerk.nl/networks/)
Dutch financial social networks from as early as 1902. 12 datasets downloadable in cvs and xls.
- UCINET datasets (https://sites.google.com/site/ucinetsoftware/datasets)
Some datasets in UCINET format.
Datasets from different fields, including literature. Some older ones.
There are also smaller lists maintained by individuals: 1, 2. You should probably check them as well. As well as Indiana University list and Pajek databases.
If you have suggestions of what should be added to the list, please comment.