Who And Why I Follow Back on Twitter

Catching up on some work this morning and going through new people that started following me over the past two weeks.  I've got my account setup so I get email notification when someone follows me and I look at each one, determining whether I want to follow back. Out of the 302 new followers I picked up in the past couple of weeks, I followed back only 27 this morning. That's only 8.95% and it is pretty typical.

Here's how I personally sort this stuff out:

When someone follows my feed I've got Twitter setup to send me an email notification.
I've got my email client (Thunderbird) setup to automatically move those Twitter email notifications to a separate Twitter folder. When I have some time (like this morning) I go through the notifications, determining whether I want to follow back. Here's my follow-back determination procedure:

1. I've got Thunderbird setup to preview email. The first thing I look for is a name (a person) attached to the account. If I don't know your organization and there is no name listed, I'm probably not going to follow back. Some details:

• I try and only follow back those with similar interests, these interests can be both work and hobby related. If you are a business, organization, academic institution or individual involved in Science, Technology Engineering or Math (STEM) I'm definitely following you back. I'll also follow you back if you are focused on one of my hobbies - for example - saltwater flyfishing. 
• Sorry but religion and politics are always a do not follow back red flag for me. I know many use Twitter and other social media for this kind of stuff and I don't have a problem with that. It's just not what I personally use it for.

2. If I like what I see in the email preview I'll click the link to your feed and take a look at the last 5 or so posts. If it is junk - spam, any hint of profanity, etc. Done - I'm not following you. The best chance for a follow back is if you have something posted I'm interested in. Maybe it is a short description with a link to an interesting post on the web. If it is something I really like and retweet it, you are definitely getting a follow back.

3. There are some exceptions and I typically follow back the following:

• Local businesses (not based on religion or politics). This includes my favorite Pizza shop in Western Massachusetts. 
• Known organizations, like the National Science Foundation (of course!)
• Some celebrities - how could you not follow back someone like Weird Al Yankovic? 
• Old friends and sometimes friends of friends if I can sort the connections out. 

4. Once I start following you - if I do see any spam, profanity, religion, politics I'm un-following you. I also occasionally go in and cull the list of people I follow and this is the kind of stuff I'm looking for.

 So..... back to my experience today - only 27 follow backs out of 302 new followers..... 8.95%. Yes - there is a lot of junk out there but..... mixed in with the junk there is a lot of good stuff.

You can follow me on Twitter at www.twitter.com/gsnyder

Wavelength Division Multiplexing (WDM)

In my last legacy Public Switched Telephone Network (PSTN) post I covered Statistical Time Division Multiplexing (STDM).  In this post let's take a look at Wavelength Division Multiplexing (WDM and DWDM) methods.

As bandwidth requirements continue to grow for both the legacy Public Switched Telephone Network and the emerged Internet/IP network most of the high bandwidth backbone transmission is being done with fiber optics and a method called Wavelength Division Multiplexing or WDM. WDM functions very similarly to Frequency Division Multiplexing (FDM). With FDM different frequencies represent different communications channels with transmission done on copper or microwaves. WDM uses wavelength instead of frequency to differentiate the different communications channels.

Wavelength

Light is sinusoidal in nature and wavelength, represented by the Greek letter lambda (λ) is a distance measurement usually expressed in meters. Wavelength  is defined as the distance in meters of one sinusoidal cycle.

Wavelength Measurement

Wavelength indicates the color of light. For example, the human eye can see light ranging in frequency from approximately 380 nm (dark violet) to approximately 765 nm (red). WDM multiplexers use wavelength, or color, of light to combine signal channels onto a single piece of optical fiber. Each WDM signal is separated by wavelength “guardbands” to protect from signal crossover. One of WDM’s biggest advantages is that it allows incoming high bandwidth signal carriers that have already been multiplexed to be multiplexed together again and transmitted long distances over one piece of fiber.

Wavelength Division Multiplexing

In addition to WDM systems engineers have developed even higher capacity Dense Wavelength Division Multiplexing (DWDM) systems. Just this past week, Cisco and US Signal announced the successful completion of the first 100 Gigabit (100G) coherent DWDM trial. As backbone bandwidth requirements continue to grow these WDM and DWDM systems are significantly reducing long haul bandwidth bottlenecks.

Podcast - Why We Are Not Google: Lessons from a Library Web site Usability Study

Back in September I had the chance to interview Troy Swanson, an Associate Professor / Teaching and Learning Librarian at Moraine Valley Community College in Palos Hills, IL. In the interview we discussed a paper he published with Public Service Librarian Jeremy Green, also at Moraine Valley Community College. Here's the abstract from that paper published at Elsevier's ScienceDirect.

In the Fall of 2009, the Moraine Valley Community College Library, using guidelines developed by Jakob Nielsen, conducted a usability study to determine how students were using the library Web site and to inform the redesign of the Web site. The authors found that Moraine Valley's current gateway design was a more effective access point to library resources than a mock-up site which incorporated a central-search box on the site homepage. This finding stands in contrast to the observed trends of library Web site design that emphasizes a “Googlized” search.

Troy and Jeremy's findings are very interesting, especially if you are managing/modifying an existing site or are considering creating one. 

You can listen here:

Here's the links Troy refers to in the podcast:

The Next Level (Blockbuster article)by James Surowiecki

• http://www.newyorker.com/talk/financial/2010/10/18/101018ta_talk_surowiecki

useit.com: Jakob Nielsen's Website

• http://www.useit.com/

The Googlization of Everything (book review)

• http://www.googlizationofeverything.com/

Why We Are Not Google: Lessons from a Library Web site Usability Study

• http://www.sciencedirect.com/science/article/pii/S0099133311000280

*******

If you have iTunes installed you can listen to and subscribe to our podcasts by clicking here.

Digital Multiplexing - Statistical Time Division Multiplexing

In my last legacy Public Switched Telephone Network (PSTN) post I covered Time Division Multiplexing (TDM). I described how TDM works and why it does not efficiently use bandwidth. In this post let's take a look at Statistical Time Division Multiplexing (STDM or STATDM or STAT MUX), a much more efficient way to multiplex.

A Statistical Time Division Multiplexer (STDM or STATDM or STAT MUX) does not assign specific time slots for each device. An STDM adds an address field to each time slot in the frame and does not transmit empty frames. Only devices that require time slots get them. 

STDM uses dynamic time slot lengths that are variable. Communicating devices that are very active will be assigned greater time slot lengths than devices that are less active. If a device is idle, it will not receive any time slots. For periods where there is much activity STDMs have buffer memory for temporary data storage. 

STDM Multiplexing

Each STDM transmission carries channel identifier information. Channel identifier information includes source device address and a count of the number of data characters that belong to the listed source address. Channel identifiers are extra and considered overhead and are not data.  To reduce the cost of channel identifier overhead it makes sense to group large numbers of characters for each channel together.

In my next legacy PSTN post I'll cover Wavelength Division Multiplexing (WDM).

Broadband Divide Continues

Earlier this week, the Department of Commerce's Economics and Statistics Administration (ESA) and the National Telecommunications and Information Administration (NTIA) released a study titled Exploring the Digital Nation: Computer and Internet Use at Home. The study analyzed 54,000 households using 2010 census data. Here's some details from a blog post at speedmatters.org:

• 68 % of households used broadband in 2010.

• Broadband adoption rates are slower that mobile.

• Households with lower incomes and less education, as well as Blacks, Hispanics, people with disabilities, and rural residents, were less likely to have Internet service at home.

• Seventy percent of urban households had broadband at home, compared to 57 percent of rural households.

• Less than half (43 percent) of households with annual incomes below $25,000 had broadband access at home, while 93 percent of households with incomes exceeding $100,000 had broadband.

Here's more from the study report:

• As of October 2010, more than 68 percent of households used broadband Internet access service, up from 64 percent one year earlier. Approximately 80 percent of households had at least one Internet user, either at home or elsewhere. 

•  Cable modem (32 percent) and DSL (23 percent) ranked as the most commonly used broadband technologies. Other technologies, including mobile broadband, fiber optics, and satellite services, accounted for a small, but growing, segment of households with broadband Internet access service.

• 2000s – continued to decline from five percent in October 2009 to three percent one year later.

• Over three-fourths (77 percent) of households had a computer – the principal means by which households access the Internet – compared with 62 percent in 2003. Low computer use correlates with low broadband adoption rates.

• Broadband Internet adoption, as well as computer use, varied across demographic and geographic groups. Lower income families, people with less education, those with disabilities, Blacks, Hispanics, and rural residents generally lagged the national average in both broadband adoption and computer use. For example, home broadband adoption and computer use stood at only 16 percent and 27 percent, respectively, among rural households headed by a Black householder without a high school diploma. Also, households with school-age children exhibited higher broadband adoption and computer use rates than other households.

• The differences in socio-economic attributes do not entirely explain why some groups lagged in adoption. Broadband Internet adoption disparities decrease when regression analysis holds constant certain household characteristics, such as income, education, race, ethnicity, foreign-born status, household composition, disability status, or geographic location. For example, the gap with respect to broadband Internet adoption associated with disabilities decreases from 29 to six percentage points when controlling for income, education, age, and other attributes.

• The most important reasons households without broadband Internet or dial-up service gave for not subscribing were: (1) lack of need or interest (47 percent); (2) lack of affordability (24 percent); and (3) inadequate computer (15 percent).

• Households reporting affordability as the major barrier to subscribing to broadband service cited both the fixed cost of purchasing a computer and the recurring monthly subscription costs as important factors. Our analysis of the expanded CPS data suggests that work, school, public libraries, and someone else’s house were all popular alternatives for Internet access among those with no home broadband Internet access service. Not surprisingly, individuals with no home broadband Internet access service relied on locations such as public libraries (20 percent) or other people’s houses (12 percent) more frequently than those who used broadband Internet access service at home.

The study also describes the $7 billion Recovery Act funding directed towards broadband in the U.S. Be sure to check out the complete study document linked here.

Digital Multiplexing - Time Division Multiplexing

In my last legacy Public Switched Telephone Network (PSTN) post I covered analog or frequency multiplexing. Frequency division multiplexing is now considered obsolete technology on the telecommunications network. Analog signals are more sensitive to noise and other signals which can cause problems along the transmission path. They have been replaced with digital multiplexers. 

Digital signals are combined or multiplexed typically using one of two techniques; Time Division Multiplexing (TDM) and Statistical Time Division Multiplexing (STDM). Let's cover TDM in this post.

Time Division Multiplexing allows multiple devices to communicate over the same circuit by assigning time slots for each device on the line. Devices communicating using TDM are typically placed in groups that are multiples of 4.

Each device is assigned a time slot where the TDM will accept an 8 bit character from the device. A TDM frame is then built and transmitted over the circuit. Another TDM on the other end of the circuit de-multiplexes the frame.

TDM Framing

TDM’s tend to waste time slots because a time slot is allocated for each device regardless of whether that device has anything to send. For example, in a TDM system if only two of four devices want to send and use frame space, the other two devices will not have anything to send.

TDM Framing Showing Wasted Slots

They do not require frame space but their time slot is still allocated and will be transmitted as empty frames. This is not an efficient use of bandwidth.

In my next legacy PSTN post, I'll cover statistical time division multiplexing (STDM), a much more efficient way to use bandwidth.