I'm starting an online business targeted at a particular demographic and interests so I would like to produce content targeted at what this particular target market are actually searching for.
Google Ads allowed me to refine my target audience to the exact categories (demographics and interests) I needed but I couldn't tell me what that category of people tend to search for except for the tiny subset that happens to click on one of my ads which is very rare given I am just starting with a small budget. I would like to know the most popular search terms for everyone in the categories I specified not just those who happened to click on my ads.
I tried Google Trends, that told me the popularity of a particular search term for a given country but that's too broad - I need to narrow it down to a particular city, age group, parental status and interests. Google Trends also helped me find popular related search terms given a particular search term so I could try using that to see if there are any common popular related search terms related to my guesses but I could miss terms related to terms I never thought of.
I could try producing content across a rage of topics which I think my target audience might be interested in and then analyse the results using Google Ads but that could be a very expensive trial and error process and I might miss more popular topics which I never thought of.
Of course I could try to ask my target market in person directly (by interrupting people in the street!) but that would be very expensive for me because I would have to travel to and stay at the location where my online business is targeted, hoping to meet people with the exact same demographic and interests that I am looking.
I'm sure there must be a way to figure this out using the the Google search analytics. Essentially, all I need is a list of most popular recent Google search terms for a particular location, demographic and interests group in Google Analytics. Could anyone help me understand how to get this list?
Here are a few considerations, even if you found an answer.
Take a look at the AdRoll platform. Here's a potentially helpful article from them about target audience and demographics.
A recent article about AdWords demographic targeting. An older looking article, connecting demographics to search queries, but page's source code suggests an update this year.
Last but not least, you're probably eligible to talk with a Google Small Business Advisor.
Related
I'm looking for a source for old weather forecasts--yesterdays, last months, last years. For major cities in US.
Seems like it's easy to find future forecasts, and historical actual data, but not historical forecasts.
The product you're probably looking for is the National Digital Forecast Database, the gridded system the NWS uses to input most of its forecast. There's no API that I know of, but there are archived data files in places like here. This NWS page on degrib also offers some potential hints on what you may need.
The NWS does still also issue some specific point forecasts for certain locations, specialized forecasts for events like fires, plus forecast discussions, warning text, etc. If those are the types of things you are looking for, it may be a bit more of a slog to dig through and piece together find the product identifiers and archive resources you want. Iowa State offers a tool for accessing some of the past data, but only by office. You also may want to dig into some of the text products on their MTArchive site, particularly perhaps the Public files - the specific data is less organized, yet the simple layout may make it more straightforward to find what you need. This StormTrack thread may offer one final rabbit trail towards finding archives of NWS text products.
As mentioned in comments, you may also find there are additional users with useful input on the Earth Science Stack Exchange Beta community.
I am trying to create an app that will help users find restaurants/movie theaters/malls/etc. to hang out based on ratings and distance. Other than just the place itself, I would also like to know more detailed information about the place. For example, if I were to look for parks, I would also like to know if theres a basketball or tennis court there. Ratings and popularity would also be an important aspect to prioritize suggestions.
After looking through all three of the APIs, I could not really find any substantial differences other than their search limits. Could anyone really differentiate each API for me? Maybe even recommend one based on my specific need?
Thanks!
The Foursquare API would fit this use case perfectly because you can supply very specific filters through the API. Also, they have extensive coverage around the world, unlike Google or Yelp.
I would check out the venues/explore endpoint and use a categoryId of Parks. You can use a query parameter of "basketball" or "tennis" to find parks that have courts for these.
I found a number of similar questions on SO but they are all are either 2+ years old or aren't exactly what I am looking for.
All I would like to do is obtain a list of twitter users whose bio/profile contains certain terms (scientist, democrat, 'dog lover', etc.).
I've considered using a google site search but so far the results are incredibly noisy.
Any suggestions would be much appreciated!
CS
The Twitter API supports a People Search similar to the website's "Find on Twitter" search feature. Although you can not directly search using only profile descriptions, it appears that the description content is used as part of the search space. If you can think of a way to narrow down your results even further by directly searching the returned users' descriptions, you should be able to do what you're looking for. Check out the Twitter API documentation for more info.
Example:
Try searching for "husband father of three", and you get these results, which obviously are returned because of the profile descriptions.
I have used one tool to search twitter profiles using keywords and many advance filters. I love the information which has been provided by the FollowerSearch tool. The information was very specific, which helps me to analyze the public twitter profiles.
One of the best tools for quickly searching among the 800 million public Twitter accounts in the database is FollowerSearch.
With FollowerSearch, you can quickly conduct searches for Twitter influencers and Twitter bios across its massive database of more than 800 million Twitter profiles. You may look for Twitter profiles based on information like their location, line of work, number of followers, etc.
Twitter Influencer Profile Search
A Twitter bios search will assist you in simplifying the process, whether you're looking for influencers or new talent. You can discover Twitter folks who share your interests. Find out exact information on all the accounts whose bios contain your search term.
Identify key accounts and Twitter influencers that have required terms in their Twitter bios.
Look up new and budding talent.
Find Twitter users with similar interests.
Search Twitter profile or Search Twitter bios for any desired term.
I created a tool that does exactly what your looking for. Find70 let's you search for twitter profiles by their twitter bio. In fact, you can set up as many search filters as you want and define your own weighting for each filter. In your example above, you could search for: scientist, democrat, 'dog lover' and it would return all the accounts that have those in the bio. This can be combined with other filters too. Here it is http://www.find70.com/?t=stack
This is my first time dabbling in NLP so please excuse my ignorance. I'm looking for a method to extract interests/likes/hobbies from users' social profiles. Here is an example where all the interests/likes/hobbies are in bold:
"I consider myself a pretty diverse character... I'm a professional
wrestler, but I'd take a bullet for Wall•E. I train like a one-man genocide machine in the gym, but I cried at
"Armageddon." I'll head bang to AC/DC, and I'm seriously
considering getting a Legend of Zelda tattoo. I'm 420-friendly. I
like to party it up with the frat crowd one night, hang out with
my Burning Man friends the next, play Halo and World of
Warcraft the next, and jam with friends that aren't any younger than
40 the next. My youngest friend is 16, my oldest friend is 66. I'll
sing karaoke at the bars, and I'm my friends' collective
psychiatrist/shoulder."
The profiles are plain text. There are no meta tags or ids associated with any of it, it's just a paragraph of text.
My naiive idea was to take each noun and match it against Freebase to see if it's an activity/artist/movie/book etc. The problem is that although most entities mentioned will be things the user likes, she will also mention things she doesn't like and I have no means of distinguishing the 2.
I have 2 questions:
What sub field of NLP should I be looking at? Some googleable algorithms/techniques/authors would be greatly appreciated.
How hard is this problem?
Thanks!
First, unless using NLP to do this is a particular objective for you, check your problem domain to see if you can avoid it completely.
For instance:
do these profiles have tags (supplied either by the Site or by the
user)?
what does the Site's API make available (assuming that's how you are accessing this data; if you are scraping it, then this doesn't of course apply)? A good example, Facebook. if you read a user's posts, you'll see words like "wrestler", "karaoke", etc. but if you look at what fields are exposed via the Graph API, you'll see that these activities nearly always have an associated FB ID.
I am not a specialist in this field, but I can recommend a couple of resources directed to NLP and which are accessible to the non-specialist or novice. The first is a text processing API. This simple web service uses REST and JSON IO. It is free and seems to have a fairly large rate limit.
This API appears to rely heavily on the excellent Natural Language Tooolkit (NLTK) which is a mature stable library in python, that includes modules directed to the problem in your Question, e.g., Sentiment Analysis, Tagging and Chunk Extraction, etc.
Which particular sub-domain is most relevant to solving the Question in the OP? I don't know, but I suspect there's a module somewhere in the NLTK that does what you need. Finding that module is hopefully just a matter of skimming the API Documentation (which is organized by module); reading the Getting Started section which contains an excellent survey of NLTK's modules as well as demos for all of each of them.
I am trying to build a site that searches a database of user comments for the most often mentioned names of movies. However, with certain movie titles like Up and Warrior(2011), there are far too many irrelevant results and I want to only search for the title in threads about movies or else make sure it's mentioned in the right context. Is there a more generalized question that this problem is a subset of (I'm sure there is but google yielded nothing so far).
working out the context of a chunk of text to determin whether the word "up" is refering to a film or not is, unfortunately, something only a human can do at the moment.
have a look at amazon's mechanical turk service, you can pay people to search thru the text for you. this might not be great if you are trying to offer a free service however.