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What Twitterers Are Giving up for Lent (2021 Edition)

February 20th, 2021
A word cloud from wordart.com features "Twitter," "Alcohol," "Social Networking," "Chocolate," and "Meat" most prominently.

This year, the usual trio of Twitter, alcohol, and social networking led the list. But current events influenced the list this year more than most. Radio personality Rush Limbaugh‘s death on Ash Wednesday led many to comment that they were giving him up for Lent, landing him at #7. A major winter storm (#62, snow and #77, winter) in Texas (#34) knocked out electricity (#5), water (#35), and heat (#68) for millions of people. Finally, the global pandemic (#23, covid) elevated topics like going to the pub (#24) and suppressed others, like eating out (#75). Zoom (#63), a videoconferencing service, appeared for the first time. “Executive orders” (#53) refers to a satirical tweet about U.S. President Biden.

This year’s list draws from 24,312 tweets out of 557,560 total tweets mentioning Lent.

COVID-19

The global coronavirus pandemic led to jumps in several topics, most notably “going to the pub,” which was almost as popular as “COVID,” and was followed closely by food pickup and delivery.

COVID + the pandemic is at the top, followed by going to the pub, takeout + doordash + uber eats, masks, and lockdown.

Social Media

In the battle of the social networks, TikTok has almost overtaken Instagram, while Snapchat fell below Tinder. Facebook, not shown on this chart because it makes the chart harder to read, was once dominant and is now only just above Instagram.

Instagram is just ahead of TikTok, which are far ahead of Tinder and Snapchat.

Fast Food

Fast food is down across the board.

Chick-fil-a is down but retains its lead, followed by Chipotle, McDonald's, Dunkin, and Taco Bell.

Top 103 Things Twitterers Gave Up for Lent in 2021

1.Twitter911+2
2.Alcohol895-1
3.Social networking687-1
4.Lent515+2
5.Chocolate4760
6.Meat337-2
7.Rush Limbaugh306 
8.Swearing250+3
9.Men242+4
10.Sex225-2
11.Coffee214-4
12.Sweets213-2
13.Giving up things188+14
14.Catholicism185+9
15.Electricity178+99
16.Soda174-7
17.Fast food167-5
18.Religion154+6
19.School140-2
20.Marijuana1380
21.Sugar136+1
22.Chips123-3
23.Covid116 
24.Going to the pub115 
25.Bread115-7
26.Smoking114+5
27.Facebook113+3
28.You111-13
29.Work102-13
30.Life99-2
31.Instagram99-2
32.Tiktok96+1
33.Booze94+12
34.Texas92 
35.Water87+61
36.Masks85 
37.Online shopping85+24
38.Homework83+5
39.Hope82+15
40.Living80+36
41.Takeout77+26
42.Breathing75+17
43.Beer71-22
44.Wine71-4
45.Power61 
46.Candy60-12
47.Food59-1
48.Him59+6
49.Depression58-14
50.Shopping55+7
51.Lying53-3
52.Executive orders53 
53.Virginity51-28
54.Liquor51-16
55.Cookies51-2
56.Starbucks51-26
57.Red meat50-18
58.Christianity49+18
59.Junk food49-17
60.Procrastination490
61.Anxiety47-18
62.Snow46+47
63.Zoom44 
64.Rice44-14
65.College42-28
66.Sobriety41-8
67.Lockdown41 
68.Heat40+44
69.Carbs40-28
70.Pancakes40+3
71.Caffeine40-24
72.Donald Trump40-22
73.Masturbation39-24
74.Desserts38-3
75.Eating out38-22
76.Simping36-34
77.Winter36+28
78.Ice cream34-14
79.Lint34+1
80.God33+5
81.Cheese33-30
82.Negativity33-22
83.People32-34
84.Complaining32-28
85.Being alive32+19
86.Church31-16
87.Coke29-25
88.Pussy28-22
89.Boys28-57
90.Pizza28-29
91.Sleep28-8
92.My will to live28-11
93.Amazon27-1
94.Sarcasm26-5
95.Hate26+15
96.Snacking25-15
97.Sanity240
98.My job24-44
99.Cake23-22
100.Dairy22-56
101.The pandemic22 
102.Chick Fil A22-47
103.Baseball22+9

Top Categories

1.food3,419
2.technology2,305
3.smoking/drugs/alcohol1,613
4.irony1,341
5.habits1,198
6.relationship804
7.religion528
8.sex476
9.health/hygiene442
10.school/work414
11.celebrity313
12.politics242
13.weather213
14.shopping172
15.money125
16.entertainment106
17.sports48
18.clothes15
19.possessions12

Posted in Lent | Comments Off on What Twitterers Are Giving up for Lent (2021 Edition)

Track in Real Time What People Are Giving Up for Lent in 2021

February 15th, 2021

See the top 100 things people are giving up for Lent in 2021 on Twitter, continually updated through February 19, 2021. You can also use the Historical Lent Tracker to see trends since 2009, though 2021 is still in flux, so I wouldn’t draw any conclusions about 2021 yet.

As I write this post, with about 593 tweets analyzed, perennial favorites “alcohol,” and “twitter,” and “social networking” lead the list. I expect to see tweets this year related to the global pandemic. And will TikTok make the top ten this year?

Look for the usual post-mortem on February 20, 2021.

Posted in Lent | Comments Off on Track in Real Time What People Are Giving Up for Lent in 2021

What Twitterers Are Giving up for Lent (2020 Edition)

February 29th, 2020

This year's word cloud is from wordart.com because wordle.net no longer works for me.

This year alcohol topped the list for the first time since 2017, followed by social networking and Twitter. New to the top 100 this year are “trolling” (#14) and “being toxic” (#94), following Pope Francis’s call to give up online insults. Also new are “TikTok” (#33), “simping,” or acting obsequiously on TikTok (#41), “coronavirus” (#73) (related: shaking hands), and “the streets” (#95).

This year’s list draws from 35,817 tweets out of 540,684 total tweets mentioning Lent.

Plastic

Plastic has been appearing near the top of the list for the past two years as some churches, especially in the UK, have encouraged people to give it up for Lent. This year, mentions of plastic fell precipitously, suggesting that either giving it up has become less fashionable or that people inclined to give it up already did so over the past two years. In particular, “straws” received no mentions.

Plastic dropped from over 1% in 2019 to 0.1% in 2020.

Social Media

As noted above, TikTok is the big winner here.

Snapchat continues its decline.

Fast Food

Chick-fil-A continues its march upward, while McDonald’s continues its decline.

Domino's wasn't mentioned this year.

Top 100 Things Twitterers Gave Up for Lent in 2020

Rank Word Count Change from last year’s rank
1. Alcohol 1,533 +1
2. Social networking 1,236 -1
3. Twitter 1,191 0
4. Meat 570 +2
5. Chocolate 534 -1
6. Lent 468 -1
7. Coffee 444 +1
8. Sex 432 +2
9. Soda 426 0
10. Sweets 409 +2
11. Swearing 403 -4
12. Fast food 356 -1
13. Men 336 +1
14. Trolling 330 +106
15. You 294 +3
16. Work 288 -1
17. School 284 -4
18. Bread 254 -1
19. Chips 235 +5
20. Marijuana 214 +7
21. Beer 210 +2
22. Sugar 207 -2
23. Catholicism 202 -2
24. Religion 198 -7
25. Virginity 196 +7
26. Giving up things 177 -4
27. Life 165 -2
28. Instagram 156 +3
29. Facebook 156 -3
30. Starbucks 151 +6
31. Smoking 146 +3
32. Boys 138 -2
33. TikTok 131 +89
34. Candy 122 +1
35. Depression 119 +16
36. College 112 -20
37. Liquor 112 +22
38. Red meat 106 +5
39. Wine 105 +8
40. Carbs 104 +8
41. Simping 104 +82
42. Junk food 100 -5
43. Homework 100 -3
44. Anxiety 97 +9
45. Dairy 94 +11
46. Booze 93 +10
47. Food 92 -1
48. Fried food 92 +1
49. Caffeine 86 +15
50. Lying 85 -6
51. Masturbation 85 -1
52. People 84 +3
53. Donald Trump 84 -10
54. Rice 83 -14
55. Cheese 81 -13
56. Eating out 78 +3
57. Cookies 75 -3
58. Hope 75 -19
59. Him 75 -6
60. My job 73 -7
61. Chick Fil A 70 +10
62. Complaining 67 +10
63. Shopping 65 +1
64. Sobriety 64 +3
65. Breathing 62 -24
66. Negativity 62 -1
67. Procrastination 61 -10
68. Online shopping 61 0
69. Pizza 60 -15
70. Coke 59 +3
71. Feelings 58 +24
72. Ice cream 58 -19
73. Coronavirus 58
74. Porn 56 +3
75. Juice 54 +5
76. Boba 54 -15
77. Pussy 52 -3
78. Takeout 51 -15
79. Bills 48 -9
80. French fries 48 -10
81. Church 46 -8
82. Desserts 45 -10
83. Being gay 44 +2
84. Pancakes 44 -5
85. Being a jerk online 44
86. Being single 41 +4
87. Hot Cheetos 40 -13
88. Cheating 40 -6
89. Chicken 39 -8
90. Crying 39 -10
91. Living 39 -4
92. Christianity 39 -30
93. Gambling 39 +6
94. Being toxic 38 +29
95. The streets 38 +28
96. Cake 38 -9
97. Energy drinks 37 -2
98. TV 37 -13
99. Women 37 0
100. Pasta 36 -16

Top Categories

1. food 6,259
2. technology 3,125
3. smoking/drugs/alcohol 2,767
4. relationship 2,163
5. habits 1,882
6. irony 1,364
7. sex 1,019
8. school/work 882
9. religion 647
10. health/hygiene 352
11. money 259
12. entertainment 166
13. politics 162
14. shopping 160
15. sports 84
16. weather 18
17. celebrity 17
18. clothes 17
19. possessions 16

Media Coverage

The Lent Tracker received some media attention this year:

Posted in Lent | Comments Off on What Twitterers Are Giving up for Lent (2020 Edition)

Track in Real Time What People Are Giving Up for Lent in 2020

February 24th, 2020

See the top 100 things people are giving up for Lent in 2020 on Twitter, continually updated until February 29, 2020. You can also use the Historical Lent Tracker to see trends since 2009, though 2020 is still in flux, so I wouldn’t draw any conclusions about 2020 yet.

As I write this post, with about 1,200 tweets analyzed, perennial favorites “social networking,” “alcohol,” and “twitter” lead the list. I’ve already learned a new word: simping, “the type of person who, instead of trying to attract the opposite sex through being attractive and interesting, is more sycophantic and fawning,” commonly on TikTok. It’s currently at #12, though I assume it will fall as more people start posting.

Look for the usual post-mortem on March 1, 2020.

Posted in Lent | Comments Off on Track in Real Time What People Are Giving Up for Lent in 2020

Using Declassified Spy Satellite Photos to Enhance the Resolution of Bible Maps

November 15th, 2019

In previous posts, I talked about using a digital terrain model for high-resolution Bible maps and using AI to increase the resolution of satellite photos. In this post, I’ll talk about how you can use old black-and-white but high-resolution satellite photos to enhance lower-resolution modern satellite photos, converting this:

A ten-meter Sentinel-2 satellite photo near the Dead Sea.

to this:

The same image panchromatically sharpened to an approximate two-meter resolution.

In 1995, President Clinton declassified images taken by Corona spy satellites from 1959 to 1972. These satellites operated at a resolution of up to six feet (around two meters) per pixel, a big improvement over the ten-meter imagery that the current free-and-highest-resolution Sentinel-2 program provides. However, the high-resolution Corona imagery is black-and-white, while the lower-resolution Sentinel imagery is in color. What if it were possible to combine the two?

Not only is it possible–it’s a common practice called pansharpening that you often see (unknowingly) in satellite imagery. The Landsat 8 satellite, for example, takes color pictures at a thirty-meter resolution and black-and-white pictures at a 15-meter resolution; when you combine them, you get a fifteen-meter output.

So if you take the ten-meter Sentinel imagery and pansharpen it with two-meter Corona imagery, you get something like the above image. I combined these images by hand using GDAL Pansharpen; merging them at scale is a more-complicated problem. But others have worked on it: the Corona Atlas and Referencing System run by the Center for Advanced Spatial Technologies (CAST) at the University of Arkansas actually uses Corona imagery to assist in Middle East archaeology. They run an atlas that lets you explore the high-resolution imagery as though it were Google Maps. The imagery’s age is actually an asset for this purpose; urban and agricultural development throughout the Middle East in the last fifty years obscures some archaeological sites in modern satellite imagery. CAST has georeferenced many Corona images and makes the data available for noncommercial use. The GAIA lab at UCSD also makes georeferenced imagery available as part of their Digital Archaeological Atlas of the Holy Land.

Posted in Geo | Comments Off on Using Declassified Spy Satellite Photos to Enhance the Resolution of Bible Maps

Designing for Agency in Bible Study

April 13th, 2019

Here are the slides from a talk I gave today at the BibleTech conference in Seattle. Download the accompanying handout or explore the Expanded Bible interface mentioned in the presentation.

Read on Slideshare.

Posted in Collective Intelligence, Topics | Comments Off on Designing for Agency in Bible Study

What Twitterers Are Giving up for Lent (2019 Edition)

March 9th, 2019
Social networking tops the list of what Twitterers are giving up for Lent in 2019.

This year social networking topped the list, as it did last year, followed by alcohol, Twitter, chocolate, and, ironically, Lent. Swearing fell to #7 this year from #5 last year. With the absence of a major political or social event, 2019 was a fairly typical year for what people said they would give up for Lent.

This year, 44,291 tweets (excluding retweets) specifically mentioned giving up something, up from last year’s 29,609. In all, this year’s analysis covers 491,069 tweets, up from 427,810 last year.

Plastic

Giving up plastic has become increasingly popular in the past two years. In all, 464 tweets this year mentioned plastic of some sort, which would almost bring it into the top ten.

Over 1% of tweets this year mentioned plastic.

Brexit

The one major political event occurring over Ash Wednesday involved the ongoing Brexit debate. When British Prime Minister Theresa May accepted a suggestion that British lawmakers give up the EU for Lent, it led others to tweet the opposite:

Tweets about leaving the EU and Brexit outnumber tweets about the EU.

Depression and Anxiety

It was a banner year for those who said they were giving up both:

Tweets about both depression and anxiety increased substantially this year.

Winter

Tweets about cold weather were up this year, as they are cyclically depending on the severity of winter weather:

Tweets about both cold weather last peaked in 2015.

Gossip

Pope Francis this year suggested giving up gossip for Lent, leading to an increase in the number of tweets about it:

Tweets about gossip reached a new high this year.

Relationships

Even though last year Ash Wednesday fell on Valentine’s Day, this year the percentage of people saying they were going to give up a significant other rose:

The generic 'love' fell overall, however.

Fast Food

Chick-fil-A finally surpassed McDonald’s this year, and Chipotle continues its decline:

Taco Bell could surpass McDonald's next year.

Other Updates from Last Year

Hot Cheetos finally declined. Smoking and Juuling both rose. Tide Pods look to be a one-year phenomenon, along with Fortnite. Snapchat dropped off a cliff.

Top 100 Things Twitterers Gave Up for Lent in 2019

1.Social networking1,5290
2.Alcohol1,498+1
3.Twitter1,409-1
4.Chocolate8180
5.Lent770+6
6.Meat6840
7.Swearing606-2
8.Coffee563+1
9.Soda561-1
10.Sex511+3
11.Fast food473-1
12.Sweets460-5
13.School414+2
14.Men374+6
15.Work367+11
16.College346+9
17.Religion346+15
18.Bread336-4
19.You3270
20.Plastic3120
21.Sugar2940
22.Catholicism290+15
23.Giving up things289+10
24.Beer274-6
25.Chips269-9
26.Life258+3
27.Facebook227-15
28.Marijuana224+3
29.Brexit212+47
30.Boys204-8
31.Instagram195-4
32.Virginity187+28
33.Smoking175+7
34.Candy161-11
35.Starbucks144-1
36.Junk food138-3
37.Hope128+22
38.Homework128+8
39.Rice127+8
40.Breathing125+32
41.Cheese122-5
42.Donald Trump122+18
43.Red meat121-8
44.Lying1180
45.Food113+24
46.Wine111-5
47.Carbs111-6
48.Winter110+48
49.Fried food109+1
50.Masturbation109+6
51.Gossip108+41
52.Depression105+26
53.Anxiety103+30
54.Ice cream103-4
55.My job103+26
56.Him98+10
57.Cookies98-5
58.Pizza96-20
59.People94-5
60.Dairy94-15
61.Booze92-13
62.Procrastination91-3
63.Single use plastic84-10
64.Eating out840
65.Liquor81-7
66.Juuling80-1
67.Boba79+4
68.Christianity76+15
69.Takeout75-10
70.Caffeine75-15
71.Shopping74-17
72.Negativity73-46
73.My will to live69-1
74.Sobriety68-16
75.Online shopping66-1
76.Bills64+19
77.French fries64-16
78.Lint63+6
79.Chick Fil A61-16
80.Complaining61-29
81.Sleep61-11
82.Desserts60-15
83.Church60-5
84.Coke59-16
85.Pussy59-6
86.Hot Cheetos56-25
87.Netflix55-25
88.God54-3
89.Porn53-24
90.Snapchat50-73
91.Stress50-3
92.Oxygen50+4
93.Spending50-3
94.Pancakes46-21
95.Crying46-1
96.Diet coke46-19
97.Juice45-15
98.Chicken44-19
99.Cheating43-19
100.F***boys43-43

Top Categories

This year, the top celebrity was BTS, a Korean boy band / all-consuming lifestyle.

1.food8,004
2.technology3,688
3.habits2,963
4.smoking/drugs/alcohol2,820
5.irony2,097
6.relationship1,800
7.school/work1,490
8.sex1,164
9.religion1,016
10.politics440
11.generic427
12.money353
13.health/hygiene348
14.entertainment224
15.shopping182
16.weather171
17.sports165
18.possessions54
19.celebrity24
20.clothes16

Media Coverage

The Lent Tracker received some media attention this year:

Posted in Lent | Comments Off on What Twitterers Are Giving up for Lent (2019 Edition)

Track in Real Time What People Are Giving Up for Lent in 2019

March 4th, 2019

See the top 100 things people are giving up for Lent in 2019 on Twitter, continually updated until March 9, 2019. You can also use the Historical Lent Tracker to see trends since 2009, though 2019 is still in flux, so I wouldn’t draw any conclusions about 2019 yet.

As I write this post, with about 1,500 tweets analyzed, perennial favorites “social networking,” “alcohol,” and “twitter” lead the list. If I had to guess, with an unusually cold February across much of the U.S., weather might feature more prominently this year than last year, when Ash Wednesday coincided with Valentine’s Day.

Look for the usual post-mortem on March 10, 2019.

Posted in Lent | Comments Off on Track in Real Time What People Are Giving Up for Lent in 2019

Using Machine Learning to Enhance the Resolution of Bible Maps

March 1st, 2019

In a previous post, I discussed how 3D software could improve the resolution of Bible maps by fractally enhancing a digital elevation model and then synthetically creating landcover. In this post I’ll look at how machine learning can increase the resolution of freely available satellite images to generate realistic-looking historical maps.

Acquiring satellite imagery

The European Sentinel-2 satellites take daily photos of much of the earth at a ten-meter optical resolution (i.e., one pixel represents a ten-meter square on the ground). The U.S. operates a similar system, Landsat 8, with a fifteen-meter resolution. Commercial vendors offer much higher-resolution imagery, similar to what you find in Google Maps, at a prohibitive cost (thousands of dollars). By contrast, both Sentinel-2 and Landsat are government-operated and have freely available imagery. Here’s a comparison of the two, zoomed in to level 16 (1.3 meters per pixel), or well above their actual resolution:

Sentinel-2 shows more washed-out colors at a higher resolution than Landsat 8.

The Sentinel-2 imagery looks sharper thanks to its higher resolution, though the processing to correct the color overexposes the light areas, in my opinion. Because I want to start with the sharpest imagery, for this post I’ll use Sentinel-2.

I use Sentinel Playground to find a scene that doesn’t have a lot of clouds and then download the L2A, or atmosphere- and color-corrected, imagery. If I were producing a large-scale map that involved stitching together multiple photos, I’d use something like Sen2Agri to create a mosaic of many images, or a “basemap” (as in Google Maps). (Doing so is complicated and beyond the scope of this post.)

I choose a fourteen-kilometer-wide scene from January 2018 showing a mix of developed and undeveloped land near the northwest corner of the Dead Sea at a resolution of ten meters per pixel. I lower the gamma to 0.5 so that the colors approximately match the colors in Google Maps to allow for easier comparisons.

The Sentinel-2 scene.

Increasing resolution

“Enhance!” is a staple of crime dramas, where a technician magically increases the resolution of a photo to provide crucial evidence needed by the plot. Super-resolution doesn’t work as well in reality as it does in fiction, but machine learning algorithms have increased in their sophistication in the past two years, and I thought it would be worth seeing how they performed on satellite photos. Here’s a detail of the above image, as enlarged by four different algorithms, plus Google Maps as the “ground truth.”

Comparison of four different super-resolution algorithms plus Google Maps, as discussed in the following paragraphs.

Each algorithm increases the original resolution by four times, providing a theoretical resolution of 2.5 meters per pixel.

The first, “raw pixels,” is the simplest; each pixel in the original image now occupies sixteen pixels (4×4). It was instantaneous to produce.

The second, “Photoshop Preserve Details 2.0,” uses the machine-learning algorithm built into recent versions of Photoshop. This algorithm took a few seconds to run. Generated image (1 MB).

The third, ESRGAN as implemented in Runway, reflects a state-of-the-art super-resolution algorithm for photos, though it’s not optimized for satellite imagery. This algorithm took about a minute to run on a “cloud GPU.” Generated image (1 MB).

The fourth, Gigapixel, uses a proprietary algorithm to sharpen photos; it also isn’t optimized for satellite imagery. This algorithm took about an hour to run on a CPU. Generated image (6 MB).

The fifth, Google Maps, reflects actual high-resolution (my guess is around 3.7 meters per pixel) photography.

Discussion

To my eye, the Gigapixel enlargement looks sharpest; it plausibly adds detail, though I don’t think anyone would mistake it for an actual 2.5-meter resolution satellite photo.

The stock ESRGAN enlargement doesn’t look quite as good to me; however, in my opinion, ESRGAN offers a lot of potential if tweaked. The algorithm already shows promise in upscaling video-game textures–a use the algorithm’s creators didn’t envision–and I think that taking the existing model developed by the researchers and training it further on satellite photos could produce higher-quality images.

I didn’t test the one purpose-built satellite image super-resolution algorithm I found because it’s designed for much-higher-resolution (thirty-centimeter) input imagery.

Removing modern features

One problem with using satellite photos as the base for historical maps involves dealing with modern features: agriculture, cities, roads, etc., that weren’t around in the same form in the time period the historical map is depicting. Machine learning presents a solution for this problem, as well; Photoshop’s content-aware fill allows you to select an area of an image for Photoshop to plausibly fill in with similar content. For example, here’s the Gigapixel-enlarged image with human-created features removed by content-aware fill:

Modern features no longer appear in the image.

I made these edits by hand, but at scale you could use OpenStreetMap’s land-use data to mask candidate areas for content-aware replacement:

Data from OpenStreetMap shows roads, urban areas, farmland, etc.

Conclusion

If you want to work with satellite imagery to produce a high-resolution basemap for historical or Bible maps, then using machine learning both to sharpen them and to remove modern features could be a viable, if time-consuming, process. The image in this post covers about 100 square kilometers; modern Israel is over 20,000 square kilometers. And this scene contains a mostly undeveloped area; large-scale cities are harder to erase with content-aware fill because there’s less surrounding wilderness for the algorithm to work with. But if you’re willing to put in the work, the result could be a free, plausibly realistic, reasonably detailed map over which you can overlay your own data.

Posted in AI, Geo | 1 Comment »

BibleTech 2019

January 11th, 2019

If you’re reading this blog, then you’re probably interested in attending the BibleTech conference, held on April 11-12, 2019, in Seattle.

You may even be interested in submitting a proposal for a talk; if so, the deadline is January 31.

Here’s what I plan to talk about if they accept me:

Designing for Agency in Bible Study

This talk explores the theory and practice of designing a Bible study experience so that the distinctive property of digital media–interactivity at scale–enhances rather than constrains the participant’s agency, or ability to act. We’ll discuss how people’s psychological needs for competence, relatedness, and autonomy affect their approach to and expectations of the Bible and church life, and how developers can support these needs by considering agency during the design process. We’ll also look at a specific application that HarperCollins Christian Publishing has developed to put these ideas into practice and promote agency in the context of daily Bible reading, explaining how and why we transformed a product that wasn’t a good fit for print into one that feels digitally native.

Posted in Technology | Comments Off on BibleTech 2019

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