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Online paedophile activity in social media has become a major concern in society as Internet access is easily available to a broader younger population. One common form of online child exploitation is child grooming, where adults and minors exchange sexual text and media via social media platforms. Such behaviour involves a number of stages performed by a predator (adult) with the final goal of approaching a victim (minor) in person. This paper presents a study of such online grooming stages from a machine learning perspective. We propose to characterise such stages by a series of features covering sentiment polarity, content, and psycho-linguistic and discourse patterns. Our experiments with online chatroom conversations show good results in automatically classifying chatlines into various grooming stages. Such a deeper understanding and tracking of predatory behaviour is vital for building robust systems for detecting grooming conversations and potential predators on social media.
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DETECTING CHILD GROOMING BEHAVIOUR PATTERNS ON SOCIAL MEDIA
Miriam Fernandez [email protected]
Harith Alani [email protected]
A. Elizabeth Cano [email protected]
INTRODUCTION
SOCIAL MEDIA PLATFORMS
• Widely spread across the Internet.
• Quick and inexpensive tools for personal and group communications.
• No age, geographical and cultural boundaries.
• Anonymity of the users is not compromised.
http://i.huffpost.com/gen/1539078/thumbs/o-SOCIAL-MEDIA-facebook.jpg
* Source: NSPCC
INTRODUCTIONONLINE CHILDREN EXPOSURE TO PAEDOPHILES
• 12% of 11- 16 year olds in the UK received unwanted sexual messages*.
• 8% of 11-16 year olds in the UK received requests to send or respond to a sexual message*.
http://news.bbcimg.co.uk/media/images/58277000/jpg/_58277172_138045933.jpg
INTRODUCTION
ONLINE CHILD GROOMING
Premeditated behaviour intending to secure the trust of a minor as a first step towards future engagement in sexual conduct.
http://www.saferinternet.at/uploads/pics/442916_web_R_K_by_Christian_Seidel_pixelio.de.jpg
INTRODUCTION
ONLINE CHILD GROOMING
Pseudo-victims posing as minors
Predators seeking to groom minors
Chat-conversations
INTRODUCTION
ONLINE CHILD GROOMING
Pseudo-victims posing as minors
Predators seeking to groom minors
Chat-conversations
Convicted Predators
Archive chat conversation
INTRODUCTIONIDENTIFYING GROOMING STAGES PERVERTED JUSTICEPerverted Justice
Perverted Justice, http://www.perverted-justice.com/Perverted Justice, http://www.perverted-justice.com/
!
• 530 chat-room conversations.
• Involving:
A. PJ volunteers posing as minors.
B. Adults seeking to begin a sexual relationship with a minor.
INTRODUCTIONONLINE CHILD GROOMING OLSON’S THEORY OF LURING COMMUNICATION (LTC)
[1] Towards a Theory of Child Sexual Predator’s Luring Communication. L.N. Olson et al
Gain Access
Time
Approach
predator: where are you from victim: where I from or where I am now? what’s your asl?
age, gender, likes, dislikes, family..
Deceptive Trust Development
INTRODUCTIONONLINE CHILD GROOMING OLSON’S THEORY OF LURING COMMUNICATION (LTC)
[1] Towards a Theory of Child Sexual Predator’s Luring Communication. L.N. Olson et al
Gain Access
Time
Grooming
Approach
COREpredator: so do you masturbate? victim: not really that borin predator: what do you like in sex?
raise victim’s curiosity, .
INTRODUCTIONONLINE CHILD GROOMING OLSON’S THEORY OF LURING COMMUNICATION (LTC)
[1] Towards a Theory of Child Sexual Predator’s Luring Communication. L.N. Olson et al
Gain Access
Time
Cycle of Entrapment
Grooming
IsolationApproach
Deceptive Trust Development
Physical Approach
Sexual Conduct
predator: do you like to meet sometime? victim: maybe you seem cool … predator: but i'm sorry your parents home all the time victim: no
MOTIVATIONIDENTIFYING GROOMING STAGES PERVERTED JUSTICE
• Sexually abused children driven to voluntarily agree to physically approach the predator [36].
• Understanding predator’s manipulative strategies could help in educating children on how to react when expose to such situations.
RELATED WORK
• Predator detection (Kontostathis et al. [15], Michalopoulos et al.[17], Escalante et al. [6])
IDENTIFYING GROOMING STAGES
Predators/Victims chat-room conversations
• Annotation Tools (Kontostathis et al. [15])
• Empirical Analysis of child grooming stages (Gupta et al.[9])
• Discriminate child grooming from adults cyber-sex (Bogdanova et al.[2])
Online Child Grooming
OBJECTIVESDETECTING ONLINE CHILD GROOMING IN ONLINE CHAT-ROOMS
• Create classification models to identify online child grooming stages:
1. Trust development 2. Grooming 3. Physical approach
!
• Analyse discriminative features characterising these stages.
APPROACHIDENTIFYING GROOMING STAGES PERVERTED JUSTICE DATA SET
• 50 conversations transcripts
• Conversations with 83 to 12K lines.
• Predator’s sentences manually labelled by two annotators.
• Annotations labels: 1)Trust development, 2)Grooming, 3)Seek for physical approach, 4) Other.
Annotated Chat-room Conversations (Kontostathis et al[15])
APPROACHIDENTIFYING GROOMING STAGES ARCHITECTURE
Victim
Predator
PJ Conversations Preprocessing
Removing StopwordsStemming
N-gramSyntactical
ContentSentiment PolarityPsycho-linguistic
Discourse
Translation
Emoticon Chat-lingo
Feature Extraction Feature Selection
Info.Gain
Build SVM Classifiers
Trust DevelopmentGroomingApproach
APPROACHIDENTIFYING GROOMING STAGES DATA PREPROCESSING
• Irregular and ill-formed words.
• Chat slang and teen-lingo
• Emoticons. ! Generated a list of over 1K terms and definitions:
Challenges in processing chat-room conversations
APPROACHIDENTIFYING GROOMING STAGES FEATURE EXTRACTION
Feature Description
n-grams n-grams (n=1,2,3) BoW extracted from a sentence.
Syntactic (POS) POS tags extracted from a sentence.
Sentiment Polarity Average sentiment polarity of terms contained in a sentence
Content Complexity, Readability, Length.
Psycho-linguistic LIWC dimensions, based on cosine similarity of a sentence to a dictionary
Discourse Semantic Frames, describing lexical use of English in texts.
APPROACHIDENTIFYING GROOMING STAGES PSYCHO-LINGUISTIC FEATURES• Authorship profiling [12] shown that different groups of people
writing about a particular genre use language differently. • E.g. frequency in the use of certain words. • LIWC dataset [26] covers 60 dimensions of language.
STYLE PATTERNS
prepositions e.g., for, besideconjunctions e.g., however, whereascause e.g., cuz, hence
PSYCHOLOGICAL
swearing e.g., damn, bloody affect e.g., agree, dislikesexual e.g., naked, porn
APPROACHIDENTIFYING GROOMING STAGES DISCOURSE FEATURES
• Qualitative analysis [5] of PJ’s predators transcripts revealed frequent use of fixated discourse (i.e predator unwillingness to change a topic).
• FrameNet [1], incorporate semantic generalisations of a discourse.
• Covers 1K patterns used in English (e.g.,Intentionality act, Causality, Grant Permission)
APPROACHIDENTIFYING GROOMING STAGES DISCOURSE FEATURESSEMAFOR [4] to extract semantic frames from sentences.
Sentence: Your mom will let you stay home?, I’m happy
FRAME SEMANTIC ROLE LABEL
Grant Permission Target Action
you stay home
Grantee Grantor Action
you your mom stay home
Emotion Directed Target Experiencer
happy I
EXPERIMENTSIDENTIFYING GROOMING STAGES
EXPERIMENTSIDENTIFYING GROOMING STAGES FEATURE ANALYSIS Top discriminative features
EXPERIMENTSIDENTIFYING GROOMING STAGES FEATURE ANALYSIS Top discriminative features
predator: lots of luck right like your pictures i see you keep it in place and look
EXPERIMENTSIDENTIFYING GROOMING STAGES FEATURE ANALYSIS Top discriminative featurespredator: you ever had anyone
run there fingers real litely over your body
EXPERIMENTSIDENTIFYING GROOMING STAGES FEATURE ANALYSIS Top discriminative features
predator: do you want me to come ther ? good
EXPERIMENTS
CONCLUSIONS
• Psycho-linguistic and discourse features provide an insight of the mindset of predators in online grooming stages.
• Discourse patterns are effective features for the automatic classification of sentences into online grooming stages. !
EXPERIMENTS
FUTURE WORK
• Some stages of online grooming are not sequential (e.g. predator convincing child to meet in person during trust-development).
- Adding temporal features to the analysis could aid in characterising such back-forth changes on these stages.
• Characterise sexual content between teens and between adults (challenging since both involve the use of sexual content).
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