wendy house

Askimet provides the wendy house with an outstanding blog spam filtering service. Hoorah!

The service is much like an email spam filter, it puts all comments that it considers as spam in a place where I can review and delete them. Most of my blog spam is from people trying to sell loans

Every few months my blog spam folder contained a comment from a Blogger  hosted blog that was more than just Spam. It was promoting racial and gender hatred. I am suprised that since December 2010 the Google service Blogger, has been  prepared to host this blog that:

• Spam other blogs
• promotes hatred based on gender stereotyping (e.g. get a more obliging wife from India)
• promotes hatred based on racial characteristics (e.g. Philipino women are ok)

I’ve twice reported the blog, for abusing the Blogger behavioural code by spamming and hatred, using the Blogger ‘Report Abuse’   facitility. It’s still there.  My opinion of Google continues to dive while they continue to knowingly host a blog that the awesome Askimet recognises as a spam source and normal people recognise as promoting gender based hatred

Poor show Google

Maybe you’d like to let Blogger know how you feel about this blog, you can report it here

While standing in the isle of a FGW commuter train from London Paddington I watched the young man seated beside me using his Blackberry phone. It looked like a mini Windows 95 – text-menu list overload! My gut reaction was yuck! The young man navigated the text-heavy grey menu with impressive speed. Clearly an experienced user.

Some of the things I love about my Android HTC desire are the way the designers have managed to

• Use pleasing interaction styles -  I can gesture with flicks, stretches, squeezes. I can drag and drop all sorts of things across screens. I can use short and long presses on the screen to find different button behaviours. It’s fun to explore and learn
• Create a simple, versataile information architecture. I don’t have to learn then relearn where everything is because everything is in a sensible place that’s easy to find and find again. The navigation system is clear and simple
• Allow me to easily find and install useful, innovative, fun, relevant Apps. It’s my phone and it does what I want it to do!
• Avoid looking like Windows 95, no battleship grey, no long text menus with uninspiring fonts
• Include fun animations like the windscreen wiper blade running across the screen when its raining. I love how the designers have taken the notion of a dashboard design and then added a winscreen wiper extending the metaphor with humour. Fun!

Hoorah for Android!

Ho hum.

International rescue happens from my fabulous new Thunderbird 3.0 But, Alan, we have a problem. Almost all of the spam in the spam mail folder is from me, yes me! I’m spamming myself. Yet, my sent mail doesn’t contain the same messages. Odd. I searched the google support forums and help. I completed their multipoint point protection list at least 3 times, changed my password several times a day. Yet still I spammed myself.

Then eventually I found a knowledge base article that explained that spammers can ‘fake’ from addresses, that gmail can spot this and filter them to the spam folder. It suggested that these emails should be ignored. Three days of unnecessary angsting and password changing because the Google help and support arrangements are so difficult to navigate. Puh.

Alan, all Thunderbirds are GO!

With the message ‘help not available’ Blogger successfully manages to end my search on how to report the error message they’d given me. Time wasters.

They asked me to report it without providing a clear link to do so. I tried their support forums where I found one other message of someone reporting this error but no support on what to do about it or reassurance that Blogger is doing anything about it. I tried their help documentation with different queries and found nothing useful except this message ‘page not avialable’  that included a suggestion to use the Chrome browser.

Given this experience of their support for my encountering an error, I am not inclined to want to extend my use of their services. How can they refine services to high quality if they don’t provide an adequate error tracking, reporting system? By asking me to submit the error they implied they we’re not tracking it by any other means.

Useful of them to remind me that Chrome is a service they provide, which I might not want to use at the point they tell me they are not going to help me.

I have no idea what the worldwide statistics are for the actual use of different browsers. I do know what browsers are used by the people (IP addresses) who open Wendy House pages because Google Analytics has snooped on them and told me! (see below)

Unsurprisingly IE in all its versions is the most common browser. Obviously. Almost half these visits are made by me in the cupboard. If we remove the numbber of visits made by myself we are left with Firefox being the browser of choice for my visitors. ‘Choice’ because someone choose to install it on the computer and open it to visit the wendy house.

I understand that some people have more than one browser on their computer. For a gal like me this is potentially confusing. Where possible I like to keep  things simple; one credit card, one set of parents, one kitchen, one bathroom, one type of tea bag, one car. This simplicity reduces the everyday cognitive load of decision making. I’ve removed the need to make many daily decisions. Obviously there are some details that are significant and require reqgular decision making resources such as – which cheese? which hat? Which password?

Currently I’m toying with ‘which browser’. I am not an ‘early adopter’ of new technologies. I like to use things which lots of other people have used and found OK. Firefox is looking like the browser for me because it’s open-source, should play well with Thunderbird and lots of people that read the wendy house use it already, pressumably because it works well for them.

Google analytics provides a ‘site overlay’ that shows your website with in-place click-through statistics.   A geek like me will spend time wandering through such statistics saying ‘oOOoooo‘   and ‘Aaah‘ and ‘what does it all  mean?‘

For 4 weeks,   September 2009, Google analytics says that I had 4,681 ‘visits’.  

I rashly infer that visitors want to know something about who is writing this nonsense (8.1% on who’s wendy) or are interested in finding food (0.3%), or why I’m bothering to write about anything at all (0.2%).   Some people consider whether to comment, or why I might consider stopping people from publishing their commentson my blog, (0.1%).  

More than no-one,   some-one,   is interested in who inspired me to blog ( >0.0%) while no-one wants to  sign-up to receive notifications of my posting in thier RSS reader.

Here’s what Google Analytics says, in numbers, about what visitors click on:

• Scribbles (The Wendy House home page) = 5.9%
• Who’s Wendy = 8.1%
• Why Scribble = 0.2%
• Comment control = 0.1%
• Food foraging = 0.3%
• Credits =   > 0.0%
• RSS = 0%

I prefer the notion of ‘somone’ over the numerical representation of more than no-one  (> 0.0) looked at who I credit with inspiring my blogging.   The relationship between significant (meaning) and signifiers (often numbers) is frequently obscure and sometimes misleading.

Ho hum

Sneak preview videow   (pixellated  for privacy reasons  by google earth*) that demonstrates weekend chit-cat about a recently observed pigeon at a  House family  household ….     …can you bear the excitement?

” photograph of Google earth camera in operation on Schrocktthehouse

These are the search results produced by Googling    ’Women’   and then ‘men’  on International Women’s day (8th March 2009).      

What do you (not) see?  

How much tea did I consume while  restructuring my budget for health, beauty then pregnancy and applying for a job as a naughty hot cheating chatty woman  ?

who me?

I’m a client of Google services,

I made an error in my request,   really?   ERROR?!

I do make mistakes.    The word ‘Error’ is not one that I use to describe my mistakes.   This message is agressively accusatory and not particulalrly helpful.   Google could easily adopt a more user centric tone of voice,  less personally offensive,  if gramatically flawed,  by saying something like:

”Ooops,   Google doesn’t understand what you just did.   Can you check  to see if you made a mistake please?‘

I suppose I should be glad that I didn’t have to abort, kill or delete anything though I have occassionaly been caught aborting a kettle,   deleting cat-poop, and killing my laundry.     Shit like that does happen, and not by mistake.

Google analytics reported visitor loyalty (probably unique IP addresses?) for one week in July  2008 as significantly* BIGGER  than  during one week in January  2007.

January 2007 (July 2008)  :

• 8 (22) visitors visited between 7 and 14 times.
• 11 (27) visited 15-25 times.
• 11 (21) visited 26-50 times.      
• 0   (32) visited 51-100 times.

 Up to 29 (101)  visitors (unique IP addresses)  , other than my good-self, return frequently enough for me to assume they drop-by on a daily basis.      Out of pure, unfettered, cussedness  I am also assuming that at least half of these loyal visitors are naughty, naughty, spam-bots or or other bots of an icky nature, as opposed to pleasantly pert bots.   This assumption  still leaves me  with about 50 regular, daily, visitors who may actually be people!          

* Significance in a formal  Statistical sense identified by using Excel’s t-test function for a one-tailed, independent groups t-test that lead to the rejection  of the null hypothesis, h0, p< 0.001

 h0  ‘= there are no more people reading my blog regularly in July 2008  than in January 2007′

The result is statistically very  powerful but I have  low confidence levels in it  because of the low signal-noise ratio introduced by the way the variable (a loyal blog reading person) is operationalised (unique IP address)  that introduces a lot of noise mostly  from  bots.  

Even worse than low statistical confidence is  my  inappropriate test-selection.   Inappropriate because although the data  fulfills some of the assumtions of the independent groups t-test  e.g. parametric,    it is sufficiently naughty to potentially violate other assumptions such as truely independent groups.  

In summary,   we can probably ignore the statistical significance of the numbers because of all the non-number related issues.  

Statistical escapades put aside,  I am still convinced that  the  Wendy House  has quite a few more regular readers now than in January 2007.  

windows support answer to my query

No curmudgeonist moments for me today.

In less than a 24hr turnaround I got a response that was concise and useful.   I also tried to report my ‘bug’ to Google,   I couldn’t find a way to report it,   I used their ‘questions’ section and,   to my knowledge, no-one replied.  

Hoorah,   even people with typing-challenges,   such as myself, can easily find my blog using Google search.   Google also seems to know in advance that I might be interested in  a handyhome!

My readers are perhaps just a bit geeky, um, like me,  because they are coming  from universities,    financial institutions  and the software computing industry.  

Google analytics tells me the Network locations of computers that have reqested page-loads from the wendyhome servers.   Often these network locations are clearly consumer internet service providers,   sometimes they are not.   Here are some of the Network locations that do not look like consumer internet services grouped by primary business type.

Software/Computing

• Microsoft Corp
• APPLE COMPUTER
• Intel Corporation
• IBM
• Macafee Security
• Research Machines plc
• Hewlett-Packard Company
• Cisco Systems inc
• Opera Software asa
• Honeywell
• Eastman Kodak Company

Financial

• Credit Suisse group canada
• Fidelity Investments
• Bloomberg Financial Market
• Bank of America
• Barclays Capital (UK)
• Nat West Bank group (UK)
• First Rand Bank

Universities

• Cornell University
• Purdue university
• Leeds University (UK)
• North Carolina State university
• University of Brighton (UK)
• University of Cambridge (UK)
• University of Washington
• Charles University

Local government

• Wolverhampton city council (UK)
• East Sussex local education authority (UK)
• State of Arkansas
• State of Minesota
• State of Tennessee
• Government of South Africa

Aerospace

• the boeing company
• lockheed martin corporation
• Patrick Air Force Base

According to Google analyticals I have one regular reader in Tring.   Excellent,   Good show.   The internet reaches the person in  Tring  who is curious about middle-aged  English girlies  in the Seattle region.   hooray!   Who would have guessed?!        Welcome reader from Tring,   You know who you are…..     …isn’t Tring  ’cute’?   Oh my,   I am definitely developing Anglophile tendancies…

Blog statistics below courtesy of Google Analytics.   Google Analytics’ glossary defines visitors as:

A Visitor is a construct designed to come as close as possible to defining the number of actual, distinct people who visited a website. There is of course no way to know if two people are sharing a computer from the website’s perspective, but a good visitor-tracking system can come close to the actual number. The most accurate visitor-tracking systems generally employ cookies to maintain tallies of distinct visitors.

The method, heuristic, that Google Analytic employs to identify visitors is not detailed.  The Google Analytics graph of :: Wendy House ::  visitors  below covers a ‘normal’ calendar month and suggests that between April and May 23rd:

• 600-ish visitors  were sent by  search engines.
• 60-ish visitors return* several times per month.    Many friends and family are in this group.
• 40-ish visitors return on a daily basis.   If this is ‘people’ what troopers you are!
• 10-ish visitors, and me,  return twice a day.   Given that I regularly post only once per day 2 visits is a tad perplexing.
• no-one visits between 101-200 times per calendar month,   how odd is that?   As odd as a snake wearing a beanie in a wheelbarrow race,   that’s how odd.
• 100-ish visitors return over 200 times in one calendar month.   Super Snoopers!    Now thats just SILLY.   I don’t believe it.      I wonder what this number really suggests…

*return = becomes active after more than 30 minutes inactivity in the Wendy House.

Visitor loyalty,   fabulous idea!

The bar-chart below from Google Analytics shows that between 24th and 30th of January:

• 8 visitors (probably unique IP addresses?) visited between 7 and 14 times
• 11 visited 15-25 times, and a further
• 11 visited 26-50 times

I’m probably one person who visited 50 times

This means that I may have 29 readers (unique IP addresses)  that return frequently enough for me to guess-timate that its probably on a daily basis.   I hope this isn’t really because their browser keeps crashing when they try to open the blog….    

Of those 29 I can make a good guess about who  9 of them are… …based on both verbal and blog comments, people I’ve met…   Based on this sample of  9 people I’ll develop a “Robin the Regular Reader” persona.     I’m not assuming that these loyal visitors are the same visitors who stay for more than 10 mins when they get here.   That’s a very rash assumption.   The kind of rash that could go all red after a   good scratching…

In this second post of a sporadic  series on blog quality I hypothesize a classification of current blog visitors using some of the  Google Analytics  statistics for :: The Wendy House::   This is my first step in developing an intended user  ’Persona’,   Alan Cooper style, that will be used to improve your experience.   Hoorah!  

One of the many fancy displays provided by Google Analytics shows the average length of a ‘visit’ (a ‘session’):

By default in Analytics, a session is defined as the period of time during which visitors are interacting with your site and there has been inactivity for less than 30 minutes. After 30 minutes of inactivity, any further page views will be treated as a new session. Users that leave your site and return within 30 minutes will be counted as part of the original session

I’m hypothesising that the data in the graph below from 24hrs in  :: The Wendy House ::  shows 4 types of visitor*.     I’ll call them:

1. Pat  promptly leaves:    149 visits are less than 10 seconds.
2. Sam the speedy  scanner:   18 visitors stayed between 10 seconds and one minute.
3. Charlie checks content: 24 people stayed between 1 and 10 minutes.   I suspect these people acutally read enough of the Blog to make a reasonably well informed estimation about the relevance of its content to them.
4. Robin the reader:   13 visitors stay at the Wendy house for half an hour (10) or more (3)

*one person can appear in these statistics more than once,   by re-visiting.   Approximately 10% of the total site visits are return visits.

Google analytcis provides a web site statistics service that is free to websites that receive less than an obscenely large amount of clicks.   I set it up for the Wendy house and dropped by to look at the reports 24 hours later.  

It told me all sorts of things with graphs,  pie-charts, percentages. maps  and tables.More pretty data representations than you can shake a stick at.   The data can  even  be exported to Excel.    What does a peak at this data for Yesterday tell you?:

Below I’ve copied the top of a web page, not in Excel,   from the Wendy House statistics.   It lists the top 22 URLs (Uniform Resource Locators, or URI’s, Uniform Resource Indicators?) that have requested pages from the Wendy House during November 2006.        

Speculative interpretation of the data above:

1. The vast majority,   79% (26799/33828), of all  web-site references come from people who are already here  exploring the Wendy House  by clicking categories or  blog-referencing links within the posts.   I like this
2. At less than 1% (327/33828) Google provides the second main source of people clicking on the Wendy House.   Adding all the google numbers together (http://images.google.com/,  http://www.google.com/, http://64.233.161.104, http://64.233.179.104/)  gives a cumulative total of 327.   A substantial proportion of these references were  people looking for images.    A quick look at the search queries that bought people to this website shows they were interested in  the text and photograph in my  ”High Spirited” post.    
3. MySpace is the only Social Network that sends noticable traffic to this Blog.   4 profiles predominantly send traffic here.   2/4 profiles do this because a teenager commented on their profile including a URL to my Wendy House server stored  photograph of the High Spirited  beverage.  
   • 60 references from a 17 yr old boy in Utah.  
   • 58 references from a highly offensive-to-me female objectification for male jacking-off profile. I’ve reported it to the MySpace team  as offensive and inappropriate.      
   • 57 references from Annie, a 17yr Rhode Island  girl’s ‘private’ profile.
   • 40 references from Kate, a 17yr San Antonio girl.
4. The remainder look like websites promoting loans, gambling and drugs that I suspect remain from when I used to allow trackbacks  (now turned-off).

All came from Google variously searching for:  

• ŦĦ  
• dream suppressant
• fake street lamp
• painting small objects
• (Not Swedish but  Norwegian [thanks Raymond]  application of google): descartes skull  

3/5  searchers may well have been pleased with the results