SCIENTIA SINICA Informationis, Volume 47 , Issue 12 : 1623-1645(2017) https://doi.org/10.1360/N112017-00053

A survey of information propaganda mechanism under the cross-medium

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  • ReceivedMar 6, 2017
  • AcceptedJun 7, 2017
  • PublishedNov 30, 2017


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  • Figure 1

    Sentiment propaganda model with PRCMA multi-factors

  • Figure 2

    The analysis and evaluation framework for network group behavior

  • Table 1   The evolution clue and index for content reliability in social media network
    Class Index and clue
    Information source Basic features: visit num/prize num/rank/official ownership/domain types/topic/is ICP/is well-known/ is authenticity.
    Structure features: simpility navigation/website structure/editable reply advise/readable strength/is public aesthetic/source advertisement num/advertisement quantity/credibility other data credibility in website.
    Interactive ability: user search/information validation/timeliness of user response.
    Information content Basic features: the length of content/is spelling error/is syntax error/the reference of content and data/contain URLs/contain label/timeless of content.
    Participant degree: focus num/resport num/popularity.
    Syntax features: is true/text case/punctuation/personal pronoun/the length of content/URLs num.
    Semantic features: the professional of content/understandability/rationality/valuability/usefulness/łinebreak reliability/orientation.
    Topic The content of topic features: topic tags/topic content segmentation extraction/topic semantic features/positive scoring/negative scoring/topic sentiments.
    Topic total features: content num in topic/the average length of content/the field of topic/expression num in content in topic.
    Topic user features: average age of user/user num/validation user num/the nun of topic is referred by users/the sex of users in topic.
    Information disseminator Basic attribute features: sex/location/liveness/social platform/portrait/identity validation/level/types of user/frequenty of post/focus num/follow num/browser num of user home page.
    Preference features: the motivation writing and spreads/reputation/similarity degree.
    User behaviour features: report comment symtax/semantic/comment sentiment/supported.
    Propaganda Propaganda quantity features: propaganda degree num/max num/audience num.
    The network of content propagation: propagation subtree structure/average depth of propagation/max depth/propagation path/content dispersed structure/content delivery structure/strongly connected component/network dentisity/average clustering sparse/average path length/the distribution of degree/power law distribution/match pattern.
    A single user attribute in a network of content propagation: content dissemination form a network penetration/degree/clustering coefficient/betweenness/closeness/interest rate/the degree and the degree of correlation/weak star nodes and star effect/homogeneity.
  • Table 2   Information propaganda model evaluation index in social network
    Criterion Related definitions
    The distribution characteristics of media Information media Communication node node interaction is strong, the power index will be higher, the node of heavy tailed phenomenon is more significant, which rely on information in interactive media communication is more strong in the “opinion leaders" is more significant.
    The community of propaganda nodes The higher the clustering coefficient, the more obvious the characteristics of the network structure community, namely, the lower the speed of information transmission on the medium, but the higher the credibility of the information dissemination.
    Authority The weaker interaction between media nodes, the more stringent information dissemination channels, the higher the authority, such as: government media
    Network propagation speed and delay The speed and influence of information in different media: the propagation delay of information in the media network.
    Ability to interact online and offline The degree of network user participation and the influence of network on offline activities.
    Information content perspective Accuracy Information provides a true description; information provides a true result of subsequent events; information can accurately describe reality.
    Authority Information source authority; information based on scientific discovery.
    Goal The presentation of information presents a description of real goals; information provides an inseparable and unbiased description of reality.
    Real-time The information is timely; the information provides multiple sides of the real-time state; the information remains sufficiently fresh.
    Coverage Information covers a set of facts and perspectives; information can meet the needs of individuals or groups; information is beneficial to individuals or groups.
    The spread of motivation and influence Preference characteristics Communicators (forwarding comments and browsing frequency); forwarding (comments and browsing) topic types; spread interest tags; user type propagation researchers and fans of user types.
    Emotional characteristics Positive features: share happiness, enhance influence, reward motivation, help companies and help others motivation.
    Negative characteristics: negative emotional venting, psychological comfort, warning others, seeking compensation and revenge.
    Neutral characteristics: participation, interaction, support, community development, habitual motivation, etc.
    Reciprocal exchange capability The purpose of sharing and disseminating information is to better access to equal information resources, to reflect the influence and value of communicators, and to value the equivalence of the content of communication.
    Influence characteristics The physical attributes of network nodes, network topology attributes and network link characteristics.
    Receiver preference User perception feature Semantic content category and emotional tag of information content.
    Characteristics of interest preferences Receiver forwarding (comments and browsing), topic classification and interest tags; receiver focuses on user type and fan user type.
    Comment/Forwarding features Forwarding (comments) content syntax and semantic features; comments and content information and negative comparison; whether or not the comment supports content.