The area nestled between Eastern Rhode Island and hugging the Atlantic ocean to the cape is known as Massachusett’s Southcoast. The area is home to many communities such as Fall River, MA, New Bedford, MA, and Fairhaven, MA. These communities are also home to excellent restaurants, bars, and ice cream shops.
There are many places the Southcoast offers to eat or drink, I thought it might be helpful to map out the restaurants that I would highly recommend. I used Google Maps to map out locations that I find worthy of a visit. These locations are based on my previous experiences, and I did not choose to map any franchise restaurants and chose areas that are independently run.
While making this map, I also used different categories to distinguish various places, including dine-in restaurants, take-out restaurants, bars, and ice cream shops. You can view the map below.
I made this map manually, and only tracked my preferences for restaurants, but artificial intelligence has probably already mapped my behavior and preferences. In fact, artificial intelligence is tracking everyone’s location, and giving tools to businesses to capitalize on that data.
Locating Influencers to Map Connections
There has been a significant push lately to use location based analytics to pinpoint customers precisely. Many companies are turning to location based analytics to precisely target their customers. Businesses can send alerts, advertisements, navigation aids, and enticements to customers when they are within the business’ location.
As creepy as that is, other tools can identify and create a map of influencers in digital spaces. This week, I’ve been curious about searching location-based data through Twitter.
Mentionmap.com is a tool that marketers can use to locate possible influencers on Twitter. The data from this tool is expansive, and I can use this data to identify potential influencers who could increase my brand’s visibility.
Mention Mapping the Southcoast
I was surprised to see that the Southcoast of Massachusetts is not frequently mentioned on Twitter. Instead, the results features more data from the United Kingdom’s Southcoast. I also searched the area communities and found a tiny number of people and influencers discussing these communities. These folks also had relatively small followers.
While searching for #NewBedford, realtors, tattoo companies, and temporary work providers tend to be using #NewBedford frequently. A skincare company out of Florida also tends to use #NewBedford in their posts. These pages have a relatively small following. However, there was one influencer that appeared in my search.
I did find the New Bedford Guide, a for-profit social media re-poster with a sizeable following. If a company agrees to pay the New Bedford Guide, it could be a valuable platform to engage new audiences.
However, the New Bedford Guide frequently shares content that disparages immigrants and foreign nationals, criticizes the Black Lives Movement, and regularly uses click bait and controversial headlines to increase clicks onto the site. Anyone attempting to engage the New Bedford Guide should understand the social media’s audience and how they might perceive content.
Mention mapping proved to be quite unreliable. I found that it was difficult to find influencers in my area. The only assumption I can make is that many people aren’t using location based hashtags. I attempted to search for #NBMA instead of #NewBedford, and ended up finding a group of people using that hashtag to discuss something in Madrid, Spain.
While the tool was interesting and fascinating, it did not provide me with any real insight to what I was searching for. I really had to dig deep and search multiple hashtags and accounts to see what people were mentioning on Twitter. I also wonder how many people are actively using Twitter in this area, and the data I collect could be inconclusive.
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