移動(dòng)智能推薦情境下網(wǎng)絡(luò)成癮行為扎根研究

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Grounded Study of Internet Addiction Behavior in the Context of Mobile Intelligent Recommendation

AbstractAI-driven recommendation algorithms have been widely deployedacross mobilesocial media platforms， enablingpersonalized informationdeliverythrough learning fromusers'historical behaviorsand interestpreferences. Theresultingmobile inteligentrecommendationecosystemunderscoresthedisruptiveapplicationsofAIintherecommendation domain.While mobile inteligentrecommendationsbettersatisfyusers'information needs，theyalso exacerbateaddictiveonlinebehaviors.This study employs grounded theory to explore theunderlying mechanisms influencing userinternetaddictionwithinmobileinteligentrecommendationcontexts.First，aninterviewprotocolwasdesigned，nd data werecollected through semi-structured interviews.Three-tiercoding Was thenconducted： during open coding，l32 initialconceptsand33basiccategories wereextracted;throughaxialcoding，lOprincipalcategories wereidentified;and duringselectivecoding，atheoreticalmodelofinternetaddictionmechanismsinmobileinteligentrecommendationscenarios wasconstructed.Tefindingsrevealthatpersonaliteracyehavioralbeliefs，exteralifluences，egativemotions， andreal-worldconditions exertdirectimpactsoninternetaddictionbehaviors.Meanwhile，theinformationqualitysystem quality，andservicequalityofintellgentrecommendations indirectlyinfluencebehavioralbeliefs throughmediatingeffectsof usersatisfaction，therebyaectingaddictivebehaviors.Thisresearch，toacertainextent，elucidates thesocietal impactsofAI'sdisruptiveapplicationsinrecommendationsystems，providing theoreticalreferencesforinterventionsand governance strategies addressing user internet addiction within mobile intelligent recommendation environments.

/wordsmobilesocialmedia;inteligent recommendation;disruptive application;internetaddiction; grounded th

隨著人工智能（ArtificialIntelligence，AI）技術(shù)的快速發(fā)展和移動(dòng)社交媒體的廣泛使用，算法驅(qū)動(dòng)的智能推薦系統(tǒng)已深度嵌入移動(dòng)社交媒體平臺(tái)，對(duì)人們獲取信息的方式產(chǎn)生了顛覆性影響[1]。（剩余11704字）