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Based on our record, Google Trends seems to be a lot more popular than Parse.ly Analytics. While we know about 60 links to Google Trends, we've tracked only 3 mentions of Parse.ly Analytics. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
B: Trends are a popular topic to talk about. They can refer to the general direction or movement of something, such as fashion, technology, or culture. They can also refer to the data that shows the changes in popularity or frequency of something over time, such as Google Trends¹. Some trends that are relevant for 2023 are: - The rise of ChatGPT, a powerful natural language processing technology that can generate... Source: about 1 year ago
I read the story. I also know that if you search for Ava James and OnlyFans the story is going viral. Go to this page https://trends.google.com/home and watch the search term "Ava James" take off - I guarantee the searches will be in the thousands by tomorrow. Source: about 1 year ago
Google Trends (Free) — Analyzes the popularity of top search queries in Google Search. Source: about 1 year ago
After a quick look on Google trends it appears that place of worship shootings get more searches than school shootings actually. Go ahead and punch some in yourself. It seems that on a per victim basis, churches receive more press. The same is true when viewed as an event. If you are unfamiliar with the tool, be sure to find the correct search topic rather than search results or it will skew the data. Also adjust... Source: over 1 year ago
I am working on a project in which I will track the popularity of multiple topics over time and I want to use Google Trends - https://trends.google.com/home. Source: over 1 year ago
I've also seen parse.ly pop up a bit, I might try it to see if it's any decent. Source: over 1 year ago
Parse.ly | Python Data Engineers (NA) & Machine Learning Engineers (EU) | Remote | Full-Time | https://parse.ly Are you a Python programmer based in North or South America, interested in large-scale data processing (terabytes per month, petabytes in our archive), and making use of massively-parallel computing architectures, such as those behind Spark and Dask? Or, are you a Machine Learning Engineer in Western or... - Source: Hacker News / almost 3 years ago
Would be really useful (not to mention polite) if sources were cited when you do this. For example, I think the early points are from the parse.ly report. People might want to click through for context if you let them. Source: over 3 years ago
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