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Spam and Phishing Detection

Spam and Phishing Detection is a research topic within Information Systems. Science Explorer counts 23k research works in it since 1970. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the detection and prevention of phishing attacks, including techniques such as spam detection, machine learning, bot detection, review spam analysis, URL filtering, and defense against Sybil attacks in social networks. The research also explores behavioral analysis for identifying suspicious activities and emphasizes the importance of security education in mitigating phishing threats.

  • Phishing
  • Spam Detection
  • Social Networks
  • Machine Learning
  • Bot Detection
  • Review Spam
  • URL Filtering
  • Sybil Attacks
  • Behavioral Analysis
  • Security Education
Research works
23k
fractional, since 1970
In the world top 10%
2.3k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+44%
the tick is no change
Largest producer
India
42% of the 10 largest, 2022-now

Which countries lead Spam and Phishing Detection research?

By volume, India and China publish the most (2.6k and 1.2k works in 2022-now).

By volume, 2022-now

  1. 1 India 2.6k works
  2. 2 China 1.2k works
  3. 3 United States 1k works
  4. 4 Indonesia 271 works
  5. 5 United Kingdom 226 works
  6. 6 Saudi Arabia 200 works
  7. 7 Malaysia 162 works
  8. 8 Bangladesh 156 works
  9. 9 Türkiye 154 works
  10. 10 ?? 140 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

India: 41.8%China: 20.2%United States: 16.5%Indonesia: 4.4%6 others listed: 17.0%42%largest
India2,551 · 41.8%China1,235 · 20.2%United States1,010 · 16.5%Indonesia271 · 4.4%6 others listed1,038 · 17.0%

Shares of the rows listed above, not of the whole node.

Which institutions lead Spam and Phishing Detection research?

By volume in 2022-now, SRM Institute of Science and Technology publishes the most Spam and Phishing Detection research, followed by Saveetha University and Amrita Vishwa Vidyapeetham.

Who are the leading researchers in Spam and Phishing Detection?

The most-cited researchers publishing on Spam and Phishing Detection include Christopher D. Manning.

  1. 1 Christopher D. Manning United States 179k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Spam and Phishing Detection?

The most cited paper in Spam and Phishing Detection is "The spread of true and false news online" (Soroush Vosoughi, Deb Kumar Roy, Sinan Aral, 2018), with 8,825 citations. Next come "Support vector machines" (7,152) and "A systematic analysis of performance measures for classification tasks" (7,026).

Most cited papers
#PaperReleasedCitations
1 The spread of true and false news online Soroush Vosoughi, Deb Kumar Roy, Sinan Aral · Science 8 Mar 2018 8,825
2 Support vector machines Marti A. Hearst, Susan Dumais, E. Osuna et al. · IEEE Intelligent Systems and their Applications Jul 1998 7,152
3 A systematic analysis of performance measures for classification tasks Marina V. Sokolova, Guy Lapalme · Information Processing & Management 9 May 2009 7,026
4 VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text Cecelia Hutto, Éric Gilbert · Proceedings of the International AAAI Conference on Web and Social Media Conference paperOpen access 16 May 2014 6,006
5 A survey on concept drift adaptation João Manuel Portela da Gama, Indrė Žliobaitė, Albert Bifet et al. · ACM Computing Surveys Open access Mar 2014 3,634
All 100 most cited papers, with filters and sorting

Where is Spam and Phishing Detection research done?

The largest centres of Spam and Phishing Detection research in 2022-now are Chennai (India), Beijing (China), Bengaluru (India) and Pune (India). Among places with at least 20 works in it, it is an unusually large share of all research in Pulchowk, Vijayawada and Greater Noida.

Largest cities, 2022-now

  1. 1 ChennaiIndia 296 works
  2. 2 BeijingChina 270 works
  3. 3 BengaluruIndia 143 works
  4. 4 PuneIndia 134 works
  5. 5 CoimbatoreIndia 124 works
  6. 6 New DelhiIndia 114 works
  7. 7 DhakaBangladesh 103 works
  8. 8 HyderabadIndia 102 works
  9. 9 Greater NoidaIndia 72 works
  10. 10 ShanghaiChina 72 works

Where it is the local speciality

  1. PulchowkNP · 27.3 works15×
  2. VijayawadaIN · 58.3 works15×
  3. Greater NoidaIN · 72.2 works13×
  4. FaridabadIN · 21.2 works12×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Spam and Phishing Detection than the world average.

See Spam and Phishing Detection on the map

Where is the best place to study Spam and Phishing Detection?

Among universities, judged by research, Princess Nourah bint Abdulrahman University, King Saud University and Xi'an Jiaotong University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 19.95%fractional works in this field (log) →share of work in the world top 10% →Princess Nourah bint…Xi'an Jiaotong Unive…King Saud UniversityAmrita Vishwa Vidyap…
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Princess Nourah bint Abdulrahman UniversitySaudi Arabia 68.334.6%4.4×9 +147.4%
2King Saud UniversitySaudi Arabia 64.524.9%3.1×23 +30.2%
3Xi'an Jiaotong UniversityChina 56.934.0%1.2×16 +71.2%
4Amrita Vishwa VidyapeethamIndia 55.87.8%15.0×60 +102.5%
5Vellore Institute of Technology UniversityIndia 55.68.6%7.6×57 +40.4%
6Macquarie UniversityAustralia 55.030.9%3.6×10 +57.6%
7SRM Institute of Science and TechnologyIndia 54.22.6%10.8×84 +281.1%
8Carnegie Mellon UniversityUnited States 54.217.5%7.2×23 -11.3%
9Saveetha UniversityIndia 53.83.6%9.1×66 +2145.6%
10Northwestern Polytechnical UniversityChina 53.235.0%1.3×11 +78.9%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Spam and Phishing Detection, country by country

Is Spam and Phishing Detection research growing?

Output in 2022-2025 was 44% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Spam and Phishing Detection.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Spam and Phishing Detection as a percentage of every work published that year, 0.037% in 2024.

still counting0.020%0.040%0.060%Spam and Phishing Detection0.041% in 202519801990200020102020

Fractional works of Spam and Phishing Detection over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Spam and Phishing Detection9.9% in 202520102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

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